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Beyond the Numbers: How to Succeed as an Analyst, Grow in Your Career, and Avoid Burnout. Part 2

Sergo — Sun, 10 Aug 2025 16:43:11 +0000

Hi! We’re Sergey Medin and Andrey Krasovitsky, analytics team leads at Avito. In the first part of this article, we focused on how analysts can build strong relationships with colleagues and maintain a healthy work-life balance. In this follow-up, we’ll talk about how to approach problem-solving and develop professional skills.

We’ll walk through key principles of task decomposition and efficient time planning. We’ll also share practical advice on how to keep growing in analytics — even when you have little to no time for formal courses or structured learning.

All of the tips we share are based on real experience — both successes and mistakes we’ve made and learned from. We hope you find this part just as helpful as the first.

Problem-Solving

One of the most common challenges analysts face is a lack of attention to how their work is organized. In theory, many know how to structure a task—but in practice, they often dive in chaotically.

Another frequent difficulty is self-doubt. It can stem from the feeling that other teams are tackling bigger, more ambitious problems. Analysts start thinking their peers are building a “spaceship,” while they’re stuck working on something simple and insignificant.

Andrey Krasovitsky

Our team was tasked with identifying new clients with the highest lifetime value (LTV) so we could assign them personal account managers. One of our analysts suggested using an ML model to evaluate the clients. But due to a lack of confidence—or perhaps limited experience with similar tasks—the process started to stall. The analyst felt that someone else on the team could probably do a better job, and that self-doubt made it hard to focus. For the first two weeks, we saw almost no progress, as the analyst jumped straight into calculations without a clear plan. To get things back on track, we held a meeting where we broke the task down into key steps and clarified what needed to be done at each stage. We also defined timelines and risks for every phase. This gave us a structured approach and allowed the analyst to move forward gradually, improving the model step by step. In the end, we developed several model versions that passed testing successfully. Even though the final scoring wasn’t perfect, when we presented it at a team-wide meeting, it was met with a lot of enthusiasm—it actually felt like we had built that very “spaceship.”

Tip 1: Break Down the Problem — Complex Solutions Are Built from Simpler Ones

Analysts often face tasks with vague wording and unclear end goals. At the same time, stakeholders may want immediate estimates—or even demand a fixed deadline. This can be overwhelming. But instead of panicking, the key is to break the problem down into smaller parts.

Most analytical tasks fall into one of two categories:

1.Exploration — These are open-ended tasks where the goal is to uncover patterns, identify segments, or calculate an unknown metric. There may not even be a clear hypothesis at the start.

2.Development — These tasks already have a defined outcome in mind—like a model or tool that needs to be built. The objective is to figure out the path to that known result.

Sometimes, exploration leads into a development task—and sometimes it’s the other way around. But the approach to decomposition differs slightly for each.

Use the MECE principle when inputs are unclear.
This is especially useful for exploratory tasks, where the outcome may be unknown or even unknowable. That’s where the MECE principle comes in handy.

MECE stands for Mutually Exclusive, Collectively Exhaustive. It’s a method often emphasized during interviews at top consulting firms like McKinsey, Bain, and BCG.

MECE helps you structure information by splitting it into non-overlapping and fully comprehensive parts—so you can cover all aspects of a problem without redundancy.

Let’s look at an example to make it clearer:

🔍 Example: Using MECE to identify why a company’s profits are dropping
Randomly guessing possible causes usually won’t get you far. General statements like “sales dropped” or “costs increased” don’t explain much.

To understand what’s really going on, try breaking profit down into its key components. Using a MECE-style tree, you could split profit into revenue and costs.

Revenue can then be broken down into price and quantity sold
Costs can be split into fixed and variable expenses

Even within such a simple structure, we get a much clearer picture and can generate hypotheses within well-defined boundaries. For example: sales may have dropped, prices decreased, or variable or fixed costs increased.

The advantage of this approach is that each branch rules out the others—if the issue isn’t with revenue, then it must be with costs. In addition, the structure covers all possible scenarios: profit problems can only be related to either revenue or expenses.

Andrey Krasovitsky

We recently applied this approach at Avito. We needed to evaluate the effectiveness of a product, but there was no single metric available—and coming up with one right away wasn’t feasible. The product was complex and made up of many components, so it was important for us to get a holistic view across all its functions. To solve the problem, we took the product’s core user need and broke it down into logical blocks. The result was a multi-level tree structure, which immediately revealed two things: some aspects we had completely overlooked, and others didn’t yet have any metrics to measure effectiveness.

Sergo Medin

I used the MECE method in my previous role when we needed to identify and resolve issues in Yandex’s courier app.
We started by classifying all the problems:

Critical — issues that completely blocked work

Major — those that caused discomfort or inefficiencies

Minor — small annoyances that still needed attention

This helped us see what truly mattered and what could wait. Next, we grouped the critical needs into categories: interface, functionality, performance, and integrations. This made it easier for the developers to prioritize and focus on what was most important. When we discovered that many of the issues were rooted in performance, we applied MECE again: we split the problem into server-side, client-side, network-related, and platform-related issues. Digging deeper into the server-side, we found that the main bottlenecks were related to database performance, load balancing, and server configuration. As a result of this structured analysis, the developers had a clear action plan, resolved issues faster, and the entire team became more productive. The MECE method helped us turn chaos into structure—and vague problems into concrete, solvable tasks.

Try setting aside time to apply MECE decomposition to your everyday tasks. Over time, you’ll begin to see problems more structurally, and breaking them down into logical components will become second nature. This principle is helpful not only for solving individual problems but also for developing a more systematic way of thinking.

When working on complex tools or models, MECE can also be applied—but with a focus on dividing the task into sequential, mutually exclusive steps that together fully cover the entire development process.

🔍Example: How we used this principle to build a model for identifying high-potential clients

We started with a basic approach to building a machine learning model:

That initial plan was too high-level, so we broke each step down in detail. For example, “data preparation” included:

This detailed plan helped us clearly see the sequence of actions, estimate timelines, and make the work more transparent and understandable.

The MECE method allowed us to move toward our goal with clarity and avoid confusion. We started with segmentation based on business rules, then added an ML model, expanded functionality, set up proper data delivery, and reduced the time between user registration and result delivery. By tackling the task step by step and in a structured way, we were able to build a powerful solution out of simple, understandable components.

📌 Try shifting away from viewing tasks as one big block and move toward a “LEGO approach.” Think of tasks as a set of small building blocks that you can combine into a complete solution.

Tip 2: Learn to Plan Tasks and Manage Expectations

One of the most common issues when working with analysts is missed deadlines. Stakeholders may apply pressure, demanding quick results, and analysts often hesitate to propose longer timelines out of fear of seeming inefficient. As a result, they give unrealistic estimates.

Sergo Medin

We had a case where an analyst promised to build a demand forecasting model in three days. The stakeholder from the commercial team was pushing for a tight deadline, and the analyst, wanting to appear efficient, agreed—without fully considering the scope of work or potential challenges.Once the work began, it turned out that the data from the new region was incomplete, of poor quality, and access to some sources required additional approvals. At the same time, there were changes in the model parameters, which further delayed the process. By the second day, it became clear that the timeline was unachievable. The analyst ended up working nights to try and meet the original deadline, but the model was still underdeveloped. It took several more days to finalize it—and the analyst was completely drained. This situation taught us a valuable lesson: it’s better to give a realistic timeline from the start and honestly communicate all risks to the stakeholder. And if anything is unclear, ask for time to clarify—or raise concerns as soon as they arise.

To address challenges with estimation, we developed a rule:
After running several expert evaluations, we found that a realistic timeline for an analytical task is the analyst’s pessimistic estimate multiplied by two.

That pessimistic scenario should account for unexpected tasks, bugs, and last-minute change requests from stakeholders.

Learn to justify the time you allocate for a task and offer alternative solutions when stakeholder expectations are unrealistic. For example, if a task seems like it’ll take one day, but you estimate two—explain that the extra time is for verifying results.

If a task is expected to take a week, it’s reasonable to double that estimate to account for competing priorities and context switching.

And if a stakeholder demands something complex in a very short timeframe—suggest a more realistic solution. We once had a stakeholder ask for a client scoring model to be built in a month. Knowing that wasn’t feasible, we proposed a simpler segmentation based on business rules instead. This allowed us to meet the deadline while buying more time to work on a full solution.

📌 Transparency helps prevent burnout and delivers more value to stakeholders than heroic efforts to achieve the impossible. It’s better to plan for more time up front—and ideally, deliver earlier than expected. That way, the stakeholder is happy with the early result and leaves with a strong impression of the analyst’s reliability.

Tip 3: Presentation Matters Just as Much as the Analysis Itself

Analysts with strong technical skills often move up the career ladder more slowly than some of their less experienced peers. One of the key reasons? They don’t pay enough attention to how they present their work.

These specialists may feel insecure despite their expertise, and they might struggle with communication and clearly presenting their results. As a result, stakeholders may perceive them as less reliable—even if their analytical work is excellent.

Ultimately, an analyst’s workflow boils down to two parts: doing the analysis and presenting the results clearly and convincingly.

Here are a few tips for both stages:

Write clean, readable scripts that others can understand—remember, you might revisit them later, or another analyst might want to review your work.

For example, when creating an SQL script for a data mart, keep in mind that a teammate might need to inspect your logic for calculating certain columns.

If the script lacks formatting—contains long statements on one line, inconsistent spacing, and commands like SELECT written in both uppercase and lowercase—it becomes hard to follow.

On the other hand, a well-structured script with comments allows others to quickly grasp your logic and reduces the chance of errors.

Break scripts into logical blocks instead of putting all logic in one place. Using a “LEGO approach”—dividing the task into smaller, simpler parts—makes your code more understandable and easier to maintain. Write your scripts so they can be updated in six months without needing to decipher your entire thought process from scratch.

Andrey Krasovitsky

I truly felt the importance of formatting during my very first project, when I was still an intern at McKinsey. We urgently needed to prepare a presentation filled with numbers from different sources for a client. I jumped into the calculations, plugged the results into the slides, and sent the presentation to my colleagues for review. They quickly came back saying that some of the numbers didn’t match and needed to be fixed immediately. I ended up spending almost the entire night hunting down the issue—because the script lacked formatting and structure. Once I found the error, I had to go back and double-check the script for any other inconsistencies. After that, a senior colleague gave me some valuable advice: always use formatting to increase accuracy and make your code easier to work with.

A Few Tips for Presenting Your Results Effectively

Collect materials for storytelling and prepare mini-presentations or boards to showcase key data. Many analysts don’t personalize their presentations—or skip them entirely. During demo sessions, they either read directly from their scripts or tracker tasks, or try to improvise a story on the spot. These types of presentations are hard to follow, which makes it difficult for others to understand the value or provide meaningful feedback.

Prepare in advance and support your presentations with visuals. This helps make your data more digestible and easier for others to engage with.

Use a simple structure, like the STAR framework:

Situation: the context
Task: what you were solving
Action: your key steps
Result: what you achieved and what’s next

Use bullet points, add screenshots of scripts or graphs. This makes the presentation more coherent and structured.

Tailor your presentation to the audience.
To create the right materials, it’s important to put yourself in your audience’s shoes. Imagine this: you've spent months building a complex, multi-level model—handling data processing, feature engineering, and debugging. Now it’s time to share your results—with key stakeholders, fellow analysts, and friends outside of tech.

Each group needs a different approach:

🙋 Key stakeholders have many responsibilities. To them, your model is just one part of a much bigger project. They care about impact and use cases, not technical details. Prepare a concise summary with key points and takeaways. Your goal is to clearly communicate the value of the model without overloading them with information.

🧑‍💻 Fellow analysts are curious about the technical side—how and why you made certain decisions. Even though they know the tools, just showing them raw scripts isn’t enough. If the information is too dense, they might still struggle to follow. Make things simpler: add visuals, examples, and explanations.

🧍 Friends outside of IT don’t need the technical details (and much of it might be under NDA anyway). Here, it’s better to share high-level takeaways or fun behind-the-scenes moments. Focus on their interests so your story doesn’t turn into a long, dull work monologue.

Sergo Medin

Once, our team was presenting the idea of implementing RFM segmentation for our customer base to the sales managers. We thoroughly explained how the metrics were calculated, why percentiles were used, and how we validated the results with correlation analysis. We thought our explanation was clear—but for the sales managers, it was overwhelming, and they couldn’t see how the data connected to their day-to-day tasks. We took a step back, reworked the presentation, and focused on how the segmentation would specifically benefit their work. We replaced analytical jargon with the audience’s language: we showed how segmentation could help increase conversion rates, save time, and enable more precise targeting. Instead of diving into complex calculations, we used clear, intuitive categories like active clients, dormant ones, and premium customers. The difference was immediate. The managers understood the concept, started asking questions, and got involved in discussions about implementation. This experience taught us that a successful presentation isn’t about showcasing your expertise—it’s about speaking your audience’s language. Understand what matters to your listeners, highlight only the key points, and show how your solution improves their outcomes. That’s how you make sure your message is truly heard.

Tip 4: Don’t Chase Complexity

Analysts often gravitate toward using advanced, hard-to-explain methods right from the start—ones that require significant development time and are difficult for managers to understand. The problem is, when these complex projects finally launch, stakeholders are often disappointed. They were expecting perfect accuracy, but the first version of any solution rarely lives up to that. That’s why our advice is: start simple. Use business rules or basic if-else logic as a starting point.

These approaches are easy for stakeholders to grasp and explain. Their transparency also reduces criticism. Plus, they give analysts the breathing room to build a more sophisticated solution later on—one that can be directly compared to the initial version to demonstrate improvements and added value.

Andrey Krasovitsky

On one of my projects at McKinsey, we were working on personalized offers for a retail company to increase customer profitability. We started with a simple method—RFM segmentation—and implemented it quickly. That gave us extra time to develop a more advanced ML model. In the first test, the RFM segmentation actually outperformed the ML model. It wasn’t until after several iterations and improvements that the ML model finally produced better results.

Sergo Medin

At Yandex, we were working on a query clustering task. The team proposed using neural networks to analyze the semantics of search queries and identify connections between them. It looked like a promising solution—but in practice, it turned out to be overly complex, required constant refinement, and still didn’t deliver the expected results. So I suggested a simpler approach: instead of analyzing semantics, we looked at overlapping URLs in Google search results. If two queries shared at least three out of ten URLs, we grouped them into the same cluster. It took just a few hours to implement—and the results outperformed all of our previous attempts. The method was not only accurate, but also fast and easy to execute. This experience was a great reminder that complex solutions aren’t always the best. A simple but well-thought-out approach can be faster, more effective, and easier to explain. Sometimes it’s worth pausing, taking a fresh look at the problem, and trying the most obvious path first.

Tip 5: Remember — No Result Is Still a Result

From our university years, we’re often taught that every analysis or experiment should lead to a clear and measurable impact. But in reality, most experiments don’t produce striking successes—and that’s perfectly normal. These outcomes shouldn’t be seen as failures, because even an inconclusive result can offer valuable insights.

That said, in some companies, it’s easier to get good marks in a performance review by doing something simple and immediately visible—like changing a button color and boosting revenue. But from an analytical perspective, it's often more impactful to conduct a deep, comprehensive study that explains why certain metrics dropped and outlines next steps for product growth.

If you’re coming to a performance review with research that didn’t yield dramatic results, here’s what you can do:

Translate your outcomes into numbers.
Even if there’s no direct impact on revenue, you can quantify the value in terms of time saved (FTEs), work hours, potential losses avoided, or possible future gains. In complex projects, it’s worth identifying measurable indicators that help demonstrate the value of your work.

Highlight the value of the experience.
Be sure to reflect on what you learned in the process—what skills you gained, what growth areas you discovered, and which paths turned out to be ineffective.

📌 Even if an experiment didn’t produce the expected result, it still helps move the company forward. Without these attempts, progress would stall.

Growth

Not everyone is willing—or able—to spend their personal time reading articles, watching training videos, or attending courses. But that doesn’t mean your growth as an analyst has to stop.

There are other ways to keep developing your skills without turning learning into an extra burden.

Tip 1: Attend Internal and External Analytics Meetups

Many companies regularly host internal analytics sessions, and they often encourage participation in external events as well. Finding time for internal meetups is usually easy—you can often listen in while doing other tasks.

External events might require more time and focus, but that doesn’t mean you have to catch every detail or deeply understand every topic. The main goal is to broaden your perspective. Listen to what other analysts are working on and learn about different approaches. This will help you expand your toolkit, discover alternative solutions, and apply new ideas to your own tasks.

Tip 2: Learn by Searching While You Work

In today’s world, the ability to find information is more important than memorizing everything.

For example, you don’t need to keep precision vs. recall definitions in your head—you can just look them up. Being able to quickly search via Google, Yandex, or AI assistants helps not only with solving tasks but also with learning new concepts on the fly.

When and how to search for learning:

While solving tasks
If you’re working on something new or using an unfamiliar approach, take time to read up on the topic. This will help you understand the method and immediately reinforce it through practice.

During meetings and events
Team standups, demos, and conferences often surface unfamiliar tools or ideas. If something seems useful or relevant, dive into it later to understand the fundamentals and broaden your perspective.

While talking with colleagues
Working alongside experienced specialists is a great learning opportunity. If a topic catches your interest, ask for a quick chat so they can walk you through it. You’ll not only gain knowledge but also build stronger professional connections.

📌 Make the most of your time by combining work and learning. Don’t hesitate to ask questions, search for answers, and explore new topics. Developing your analytical mindset is key—technical skills will follow with practice.

In a nutshell

We hope this article was helpful and inspired you to try new approaches in your work. Here are three key takeaways you can start applying right away:

👉 Break tasks down and start simple. Divide projects into manageable steps and begin with basic solutions. This will make the process more manageable and boost your confidence.
👉 Plan realistically. Consider potential risks and allow time for reviews. Discuss deadlines with stakeholders in advance, and be ready to offer alternatives if the timeline is too tight.
👉 Tailor your presentation to your audience. How you present your findings is just as important as the analysis itself. Adjust the format: for stakeholders — keep it brief and focused on value, for colleagues — include technical details, and for friends — go for simplicity and interesting highlights.

Beyond the Numbers: How to Succeed as an Analyst, Grow in Your Career, and Avoid Burnout. Part 1

Sergo — Sun, 10 Aug 2025 16:19:51 +0000

Hi! We’re Sergo Medin and Andrey Krasovitsky, analytics team leads at Avito. Throughout our careers, we’ve often seen analysts struggle to grow — not because of a lack of technical skills, but due to gaps in soft skills.

In this article, we share practical advice that helps analysts build stronger relationships with colleagues, tackle technical tasks more effectively, make better decisions, and organize their work. We’ll also reflect on our personal experiences, including mistakes we’ve made and how we overcame them.

The article is split into two parts. In this first part, we focus on building effective working relationships and maintaining a healthy work-life balance to prevent burnout. The second part will cover problem-solving and professional growth for analysts.

Read the second part

Collaboration

Disclaimer
All our advice comes from real experience and practical examples we’ve discussed with our teams. When analysts neglect these soft skills, their growth often slows or even stops.

Unlike managers, analysts often underestimate the importance of effective communication. They focus heavily on solving problems but that alone isn’t enough. To grow, you also need to collaborate effectively—with stakeholders, managers, fellow analysts, and adjacent teams. Let’s illustrate this with a personal example.

Andrey Krasovitsky

When I worked at McKinsey, I was tasked with auditing data quality for a telecom client. I promised results in two weeks. The task was complex—large datasets, multiple stakeholders, time-consuming calculations. The task briefing was vague, so I focused on what I thought the project manager wanted. But he wasn’t an analyst. After two weeks, I had mapped the data and outlined a solution, but it didn’t align with what the client expected—and I wasn’t ready to present results.The biggest reason it failed? Poor communication with the project manager, client, and stakeholders.

Tip 1: Put Yourself in Others’ Shoes

Keep in mind that no one is as deeply immersed in the task and its technical details as the analyst. Other stakeholders might not be aware of all the complexities and nuances you're facing.

🔍 How to apply this tip in practice:
Imagine two analysts are asked to build a dashboard. Both estimate it will take three days and add the task to their sprint. As they begin working, it becomes clear the task is more complex than expected, and gathering the necessary data will be harder than they thought.

At this point, each analyst has two options:

🙅 The first analyst decides not to change the deadline and tries to solve the problems alone—staying late at work to meet the original timeline. He doesn’t update the manager because he’s too busy.

The manager starts to worry, not understanding what’s going on due to the lack of updates. They begin to check in frequently, which irritates the analyst, who sees the manager as being annoying and distracting.

Eventually, the deadline arrives—and the dashboard still isn’t ready. The analyst is frustrated with the manager’s constant reminders, while the manager is disappointed that the dashboard wasn’t delivered on time and that the issues weren’t flagged earlier. The deadline is postponed.

🙋 The second analyst, noticing the issues early, immediately schedules a call with the manager. He explains the problems and asks clarifying questions.

Together, they conclude that the dashboard will realistically take a week to build—not three days, as initially expected. The analyst then calmly completes the task.

Let’s break down what happened here. For the manager, this was just one task among many. It was assigned and estimated, and now the only way to stay updated is by checking in.

In the first case, the analyst didn’t consider the manager’s point of view and tried to handle everything alone. In the second, the analyst immediately communicated the problem, understanding that transparency is important for the manager too.

In both cases, the project deadline shifted—but only in the first case did it cause tension between the analyst and the manager. In the second, they understood each other better, the manager didn’t break any promises to others, and might have even developed greater trust in the analyst.

Andrey Krasovitsky

The ability to see a situation from someone else’s perspective is a universal skill. It improves work quality, builds trust, and has a positive impact on outcomes—including performance reviews. Let’s go back to my example with the data audit for the telecom operator. At the time, I failed to consider that the manager was overseeing five other workstreams, and this task wasn’t their top priority. I should have approached communication differently from the start and flagged the potential risks early on.

Tip 2: Learn to Push Back and Challenge Ideas

An analyst’s backlog is always full, and sprint plans are often set months in advance. Yet somehow, there’s always one more “urgent” task that needs immediate attention. In these situations, analysts usually fall into one of two groups:

🙅 Those who say “no” to any new task that wasn’t pre-planned. These tasks often get buried in the backlog and forgotten—or completed half-heartedly, just to check the box.
🙋 On the other hand, some analysts say “yes” to every request, no matter where it comes from. These folks often end up overloaded, quickly burn out, and eventually turn into analysts from the first group. By agreeing to everything, they’re forced to juggle too many tasks under tight deadlines.

The ideal approach lies somewhere in the middle. But that doesn’t mean you should aim to accept 50% of tasks and reject the other 50%. It's not about quotas—it’s about thoughtful prioritization and knowing when (and how) to push back.

Sergo Medin

I often see junior analysts take on every single task that comes their way from stakeholders. They don’t evaluate how important these tasks are to the business—they just start working on them. This rarely ends well. These analysts overload themselves with low-priority tasks, end up working overtime, get stressed, and eventually burn out. For junior analysts, it’s especially difficult to prioritize on their own or to explain their reasoning to stakeholders. Many believe that doing quality work means completing as many tasks as possible.That’s why, in the early stages, strong support from a team lead is essential to prevent burnout. Only with experience do analysts begin to truly understand the importance of prioritization.

Learn to Understand the Core of the Task
This approach helps you identify high-priority tasks and allocate your time and energy more effectively.

There’s no universal checklist—each analyst develops their own set of questions. But there’s one question you should always be able to answer: “What will change once this task is completed?”

Why does this matter? Simply telling a stakeholder “yes” or “no” isn’t enough. Your answer—either way—should be well reasoned.

If you agree to take on a task, you should clearly understand why it deserves a higher priority than others. That means understanding its business impact and value.

Deeply engaging with a request not only helps prevent burnout, but also improves your work quality, leads to better solutions, and allows you to show real analytical initiative.

If you decline a task, you should clearly explain why you can’t invest your time in it—and ideally suggest alternatives. Follow the principle: “If you reject something, offer something else.”

Often, stakeholders haven’t done proper prep work or don’t fully understand the nuances. Sometimes the task does make sense, but the analyst doesn’t have the bandwidth because more critical projects are underway.

🔍 How to apply this tip in practice:
Imagine your manager asks you to run an A/B test for a new feature. The wrong move would be to either automatically say no or agree without thinking. Why?

Some hypotheses can be tested using data you’ve already collected—no need for a new experiment.
Certain features can be launched without any experimentation at all.
The request might be a one-off initiative that won’t scale or be rolled out broadly — even if the test succeeds. For example, due to upcoming product changes.

The better approach looks like this:
1.Clarify the task:

What questions are we trying to answer?
What actions will we take depending on the outcome?
Are there any blockers to running this test?

2.Prepare thoroughly:

Estimate the potential impact.
Define the experiment’s duration.
Check if the required data is available.
Think about possible risks or constraints—seasonality, tech limitations, etc.

💡 One rule for every step: Keep asking questions until you’re crystal clear on what’s expected of you. Don’t be shy—clarity leads to better outcomes.

If your manager or stakeholder doesn’t have all the answers, help them find them. Analysts who take initiative and partially step into a product manager’s shoes are incredibly valuable.

This kind of collaboration should be a two-way conversation—not just a stream of vague requests and one-word replies.

Along the way, you may uncover valuable insights, improve the original idea, propose a smarter plan, or even find a better solution altogether.

Andrey Krasovitsky

In that data audit case, I immediately thought the proposed idea wasn’t feasible—but I stayed silent. What I should’ve done was ask clarifying questions early on, voice my concerns about the expected outcome, and push back in the right way by highlighting an alternative solution—which, in the end, is exactly what we ended up implementing. Had I done that from the start, I wouldn’t have wasted time trying to shape the solution into what the manager initially described.

Tip 3: Gather Feedback Regularly

Performance reviews are becoming more common in many companies—they’re used to assess employee performance over a given period. Based on the results, goals are set, salary decisions are made, and career development is planned.

Reviews are closely tied to career growth, but for many people, they also bring stress and anxiety. In part, that’s because the review process in some companies can be quite subjective.

Sergo Medin

When I worked as a senior analyst, my manager rarely scheduled meetings with me. I prioritized tasks on my own, coordinated directly with product managers, and simply reported back to him on what I’d completed. His typical response was something like, “Everything looks good, you’re moving in the right direction,” without digging deeper into the work itself.
Going into my performance review, I expected excellent results—above average—since all the managers I worked with were happy, tasks were completed, and in some cases, we even exceeded our goals. So I was unpleasantly surprised when I received a below-average rating. My manager explained that, after reviewing my output, he didn’t find the work complex or impressive enough from an analytical standpoint. I disagreed: for six months, he’d expressed satisfaction and never suggested any changes. But in the review, his feedback completely shifted. That’s when I decided to continue my career in another team. Now, as a team lead myself, I try to prevent situations like this. I hold regular one-on-one meetings with everyone on my team, get into the details of their projects, and give ongoing feedback. This helps them improve their results in advance and refocus if something isn’t going as planned. Thanks to this approach, half of my team has been promoted over the last six months. I strongly believe that giving feedback continuously—not just at review time—results in more engaged and motivated employees.

Andrey Krasovitsky

Build transparent communication. If deadlines are shifting, a mistake has occurred, you’re starting to feel burned out, or something is bothering you—don’t be afraid to speak up. For managers, this is important to understand your level of comfort and professional development. For stakeholders, it helps them keep projects on track. For teammates, it creates a sense of support and mutual understanding. And for you, this kind of openness helps you avoid critical situations, receive valuable advice and support, and grow professionally as a result.

Let’s look at how to communicate with your manager and colleagues to avoid situations like these and successfully navigate your performance review.

Talk to Your Manager

1.Schedule a meeting to discuss your expectations for the upcoming review, along with your career and compensation goals. Be open about your ambitions—your manager might not be aware of them unless you speak up. Talk about where they can support you, and document any agreements.

2.Build a plan together for achieving those goals, define timelines and key milestones. This is the time to assess how realistic your goals are within the given time frame. It’s important to acknowledge that some goals might not be achievable right now—and that’s okay. There could be various reasons: maybe the analyst won’t have time to deliver a key project that would support a promotion, or maybe there are important skill gaps that need to be filled to reach the next level.

If your goals turn out to be unrealistic—but you’re willing to wait—create a longer-term plan.

If you’re not willing to wait—discuss why, and work together on possible solutions. There’s no one-size-fits-all approach here; it depends on you, your manager, and your situation. The key is to reach mutual understanding and align on goals and how to get there.

In both cases, your manager can help estimate the time needed to achieve your objectives and assist in shaping an alternative plan if necessary.

3.Track progress on the plan by taking the lead in scheduling check-ins. Make these sessions as structured as possible. For example, at Avito, we use a competency matrix to identify focus areas and measure growth.
After each check-in, take notes and document agreements to make sure nothing gets missed. This approach makes your goals and responsibilities more transparent—for both you and your manager—so when the review comes around, there’s far less uncertainty.

Gather Feedback from Colleagues

You can try structuring these conversations, but in most cases, a more casual and open format leads to a more natural and honest dialogue.

Start by identifying a list of people you work closely with — especially those who may be asked to provide feedback on your performance during the next review cycle. Setting up these conversations might feel awkward at first, particularly if you're reaching out to more senior colleagues. But overcoming that discomfort brings real benefits: you strengthen working relationships, collect valuable insights for your review, and discover new areas for growth.

Keep in touch with these colleagues and ask for feedback from time to time. The key skill here is learning to accept constructive feedback. Hearing something you don’t agree with can sting—but it’s important not to argue, especially if that feedback comes from multiple people. Often, that kind of feedback is the most valuable.

Take time to reflect on why you received those comments and what you can do to improve the situation.

We also recommend keeping a running list of all the tasks and projects you've worked on during the current review cycle. It’s easy to overlook how much you’ve actually accomplished, and that can make it feel like you’re standing still while others are advancing.

But once you look back at everything you’ve done, it becomes clear that you’re growing too. That list won’t just help during your review—it’ll also boost your confidence and remind you of your professional achievements.

Well-being

In this section, we’ll talk about how to avoid burnout and work in a way that supports your physical and mental health.

Your health—both physical and emotional—should always come first. Constant stress, lack of sleep, and ignoring your body’s warning signs inevitably lead to serious consequences. No matter how important your job may seem, it’s never more important than your well-being.

Andrey Krasovitsky

There’s a common stereotype that consultants at McKinsey have no work-life balance. I can say that’s not always true—it really depends on the project. But I won’t pretend that tough projects don’t exist. I worked on one of them myself.The deadlines were so tight that we worked without weekends and slept just 3–5 hours a night. The last month felt like Groundhog Day—work from morning till night, a short sleep, then repeat. Eventually, the exhaustion caught up with me—one evening, I felt unwell and had to step away from work for a week.That experience had a serious impact on my health and forced me to reevaluate my priorities. Since then, I’ve paid much more attention to maintaining work-life balance and structuring my work in a way that protects my comfort and energy.

Tip 1: Create Comfortable Working Conditions

A comfortable work experience starts with understanding what’s making you uncomfortable. It could be task overload, poor communication with colleagues, weekend messages in team chats, or excessive bureaucracy. The key is not just to notice these issues, but to actively look for ways to solve them—instead of simply complaining.

How to improve the situation:

Talk to your manager. If you’re running into problems or feeling dissatisfied, suggest holding a retro or bring it up in a team meeting. If it’s a broader issue, consider forming an initiative group to improve processes. For example, at Avito, we have functional projects where employees from different teams work together to improve internal workflows.
Manage your workload. Be realistic about how much time a task will take and adjust deadlines as you go. If you’re falling behind, let your colleagues know instead of sacrificing personal time. To protect your boundaries, block out time for non-work activities—like meeting friends or taking a class after hours. This helps prevent overwork.

Managing your time effectively allows you to stay productive without burning out.

Watch for signs of burnout and respond early. If you notice symptoms of burnout, there are three main paths you can take:

1.Talk to your manager about how you’re feeling and try to change your current conditions, as described above.
2.Take a break or vacation to reset. People often forget that rest is a necessary part of work.
3.Consider switching roles or teams. If change doesn’t seem possible or your current team isn’t a fit, it might be time to look for something new. You can start searching while still in your current position.

Don’t be afraid of transitions—a new job can bring fresh knowledge and valuable experience.

Tip 2: Change Your Perspective on Work

To reduce stress and discomfort, it’s not enough to just create a comfortable environment—you also need to rethink how you view your work. Here are a few simple mindset shifts that can help you deal with challenges and pressure more effectively.

Remember this principle:
“You don’t know anything—and neither does anyone else.”

One of the biggest challenges early in your career is imposter syndrome. It can feel like everyone around you is a true expert, handling every task with ease—while you feel like you know nothing. We once came across an article that helped reframe this mindset. It suggested embracing two key ideas:

1.You don’t know anything.
2.Other people don’t know anything either.

What does this mean in practice?
The first point reminds us that there will always be people who know more than you—and that’s not a reason to feel insecure, but an opportunity to learn. Get used to questioning your own ideas, double-checking your assumptions, and listening to others—even those with less experience. In fact, exchanging ideas with people who think differently can be especially valuable.

When someone has been in a role for a long time, they tend to rely on familiar patterns and approaches—which can narrow their range of possible solutions.

Meanwhile, less experienced people aren’t boxed in by past solutions, and that gives them a creative edge. They’re often more open to proposing fresh, unconventional ideas.

The second point is a reminder that even the most experienced professionals don’t know everything—and they make mistakes too. You shouldn’t follow someone’s ideas just because of their title or authority. It’s okay to question and challenge what you hear.

One way to build this habit is to listen carefully to colleagues in senior positions and mentally analyze their suggestions. Then, when appropriate, start raising your questions or disagreements out loud. Over time, you’ll realize there’s nothing scary about it.

This practice benefits the entire team. It helps you build confidence and deepen your understanding of the work.

💡Eventually, you’ll start to see that no one is immune to mistakes—and your ability to think critically and stay curious is what helps you move past imposter syndrome and grow professionally.

Tip 3: Don’t Be Afraid to Make Mistakes

Mistakes are a normal part of the job—especially when working on complex calculations, research, or tasks with an unclear context. One mistake won’t make anyone think you’re less competent. What matters is how you respond to it. Here are a few tips:

Stay calm. Assess the scope of the mistake, its consequences, possible solutions, and how much time you’ll need to fix it. If someone asks for an immediate answer and you’re not ready, it’s better to ask for time to analyze the situation than to give a random or rushed response.

If you discover the mistake yourself, it’s best to come forward with a plan—or at least a suggestion—for how to fix it. This approach will reduce any negative reaction and help you feel more in control of the situation.

Reflect on what caused the mistake. Be honest with yourself: Did you misinterpret the task? Did you fail to ask enough clarifying questions at the beginning? Understanding the root cause will help you identify areas where you need to grow—and allow you to focus on developing those specific skills.

By gradually working on these aspects, you’ll become a more confident and skilled analyst.

Andrey Krasovitsky

The most important lesson I’ve learned as an analyst is this: work is just one part of life. Make time for yourself, your family, your friends, your hobbies, and the things that interest you. When you step away from work, it not only helps reduce stress—it also gives you a fresh perspective. You might spot new ideas or catch mistakes you previously missed. Take care of your physical and emotional well-being. Value your health, and don’t let work consume all your time. Don’t wait for a breaking point to realize this truth.

In Summary

We hope this article helped you look at the analyst’s role from a different angle. Here are three key takeaways you can start applying right away:

👉 Build communication based on mutual understanding.
Regularly clarify expectations with stakeholders and teammates to avoid misunderstandings and improve collaboration. Transparency builds trust and prevents conflict.
👉 Learn to prioritize tasks.
Before picking up a new task, ask yourself: “What will change if I do this?” This question will help you focus on meaningful initiatives and manage your time more effectively.
👉 Don’t forget about yourself.
Overload and burnout affect not only your health but also your productivity. If you feel burnout creeping in, talk to your manager, rethink your work approach, or take a break to reset.

These practices will help you handle your current workload more effectively and grow in your career.

In this part, we focused on communication and well-being. In the second part, we’ll cover how to approach tasks efficiently and develop your professional skills.

For Analysts: Why Proactivity Beyond Your Role Accelerates Both Business and Career Growth

Sergo — Sat, 09 Aug 2025 18:37:30 +0000

Hi there! We’re Sergo Medin, TeamLead of Sales Analytics at Avito Real Estate, and Diana Shevyakova, Senior Analyst on Avito’s Sales Effectiveness team. We work in different areas, but we have one thing in common: if there’s a way to improve a process and deliver real value to the business, we’ll do it — even if it goes beyond the boundaries of our formal roles.

In this article, we’ll share our experience: why it’s worth stepping outside your area of responsibility, how it benefits the business, and how it helps analysts grow — in skills, career, and job satisfaction. By the end, you’ll be able to apply this approach yourself: identify an area that interests you, find an initiative, build a simple solution, and see how it can impact the processes around you.

How Responsibility Grows with Your Level

The role of an analyst is evolving — it’s no longer just about delivering accurate reports. Today, analysts are expected to drive business impact: spot problems, propose solutions, and see them through to results — even if it goes beyond their formal job description.

Why does this matter? Because these are the steps that create the most value. An analyst becomes a driver of change, helping the business make faster decisions and remove bottlenecks in its processes. This benefits the company and gives the analyst visibility, growth, development — and, not least, satisfaction from their work.

Let’s look at how an analyst’s tasks and responsibilities evolve with each level — and when it makes sense to take that first step beyond your usual role.

Junior analysts are typically given clear tasks and follow instructions.
Mid-level analysts choose methods themselves and can suggest multiple approaches.
Senior analysts define the problems, build a plan, and carry it through.

At higher levels, growth is not only about digging deeper into your core tasks — it’s also about expanding beyond standard expectations. That means noticing problems outside your immediate area of responsibility — across adjacent teams — and launching initiatives that make colleagues' work easier and business operations more effective.

This approach takes initiative, flexibility, and a willingness to dive into unfamiliar contexts. But it’s exactly what sets apart an analyst who just “does their job well” from one who transforms the processes around them.

These kinds of analysts are more likely to get noticed by leadership, advance faster in their careers, and stand out in the market — because they don’t just analyze data, they create systemic improvements. In the next section, we’ll share our own experience and show where analysts can bring value beyond their core responsibilities.

What It Means to Go Beyond Your Role

Reports, dashboards, and A/B tests are a solid foundation — but real exponential growth happens in areas full of analytical opportunities that no one is tackling yet. That’s exactly where proactive analysts should step in.

For example, our work isn’t directly related to HR or PR. But knowing these teams have limited analytical support, we looked into their challenges:

HR teams may lack the resources to automate routine tasks. An analyst can help reduce time-to-hire by analyzing the recruitment funnel and identifying bottlenecks. They could, for instance, set up auto-responses for applications or build a system to track candidate status.
PR specialists might spend hours manually monitoring countless Telegram channels to catch brand mentions. An analyst can automate that process: collect data, filter for relevant mentions, and even set up notifications. This saves dozens of hours and helps the team respond faster to media opportunities.

And let’s not forget that in many teams, tasks are still done manually in Excel. Even basic automation or scripting can significantly reduce time spent and ease the burden on colleagues.

In our experience, a good initiative solves a clear pain point, delivers measurable results, and adds minimal overhead for the team. The fewer extra steps your colleagues have to take, the more likely your improvement will stick — and bring real value to the business.

In the next section, we’ll explore the benefits teams and the company gain when analysts take on more than what’s formally expected of them.

What the Business Gains

When an analyst takes initiative beyond their core responsibilities, the company sees real benefits:

Reduced costs. Automating repetitive tasks saves the team time and allows them to focus on higher-priority work.
Faster decision-making. An analyst can build an MVP faster than it would take for the task to reach the dev team. In just a few days, you can build a simple solution and test a hypothesis on real data.
Unexpected growth opportunities. When analysts step into areas previously untouched by data — like HR, PR, or L&D — new ideas emerge that dramatically improve efficiency and optimize “blind spot” processes.

But there’s another side to this, which is important to acknowledge:

The risk of a “zoo” of solutions. If everyone builds their own dashboards or scripts, it can result in scattered tools that are hard to maintain. The solution? Align on a common tech stack, regularly review what’s still relevant, and stay in sync with colleagues.
Prototype quality ≠ production quality. An analyst’s MVP might work but often won’t cover all edge cases — and that’s okay. What matters is being clear from the start: the goal is to test a hypothesis, and the dev team will later turn it into a full production solution.

Bottom line: the benefits of analyst-led initiatives are real and fast, and the risks are manageable. The key is to stay connected with engineering, use safe and maintainable tools, document your solutions, and keep improving them as you go.

And don’t forget: these initiatives don’t just benefit the company — they often kickstart an analyst’s own growth. Next, let’s look at what analysts themselves gain by going beyond their defined roles.

What Analysts Gain

We’ve seen it time and again: being proactive benefits not just the company, but the analyst as well.

Stronger motivation. Some are driven by tackling non-standard tasks, others by the prospect of career or financial growth. Either way, stepping beyond your formal role brings those goals closer.

Choosing your own project turns a task from “just another ticket” into a personal challenge: you identify a problem, define the goal, build an MVP, align with stakeholders, plan the scaling, and hand off the solution for support. This kind of initiative builds your skills as a product thinker, engineer, and consultant all at once — a powerful combination that’s highly valued in the market.

Increased visibility. You collaborate with HR, marketers, product managers, share progress updates, and measure impact together. Each of these interactions strengthens your internal network, and before long, people across the company know who you are. Leaders are more likely to trust you with new projects or greater responsibilities — because they’ve seen you take ownership and deliver results.

A stronger personal brand. Consistent proactivity is its foundation. You can present your initiative at an internal meetup, write an article about it, or use it as a case study when moving to a new team or company. Going beyond your role isn’t about taking on extra work — it’s a deliberate strategy: doing what excites you, benefits the business, and helps you grow as a professional.

How to Choose an Initiative and See It Through: Our Experience

Now let’s share our own experience — how we went from an idea to real impact by automating HR processes.
We remembered that the HR team had mentioned the tedious manual processing of responses after events. The task caught our attention, and we knew solving it would bring real value — hiring speed is critical for Avito.

Tip: Don’t wait for a perfect brief.
In teams without dedicated analysts, stakeholders rarely have a fully detailed request. Build and show a live prototype, clarify needs, and improve iteratively. Document everything you create — it’ll make handover and reuse easier. And once the impact is clear, tell the story: in the team chat, at an internal meetup, or in a blog post. That way, your initiative helps the business and boosts your own profile.

We ran a few short interviews with recruiters, mapped out the process, and prioritized the pain points. At the same time, we checked with the dev team — they acknowledged the problem but couldn’t fit a fix into the next sprint. That meant we weren’t duplicating anyone’s work — the path was clear.

The first step: scripts layered over the existing interface.
We addressed the biggest pain point with JavaScript-based Tampermonkey scripts. These scripts added new controls to Huntflow’s interface, letting HRs export up to 120 candidate cards in one click (instead of one by one), bulk-update statuses, and tag profiles.

All HR had to do was follow a link to the repository. Tampermonkey automatically checks for updates, so ongoing maintenance was minimal.

Want the details?
Full technical implementation, code examples, screenshots, and setup instructions for similar scripts tailored to your case — available in this article.

We continued exploring other pain points in HR. Once recruiters saw how much faster candidate data export had become, they asked us to automate the import of Excel files after large-scale events like weekend offer campaigns — which can generate thousands of applications.

We decided to build a standalone web service. Here are some technical details:

Backend: Python + FastAPI — handles file uploads, validates rows, calls the Huntflow API, and logs all actions.
Frontend: TypeScript + React — supports drag-and-drop for Excel files, shows progress clearly, and offers an interactive column-matching interface so any Excel format can be used.
Quality: Unit tests cover all key logic.
Deployment: The repository is easy to spin up — the solution can be deployed to another department in just a few minutes.

The result: instead of uploading one candidate at a time manually, HRs can now upload an entire Excel file with hundreds of entries to Huntflow in just 60 seconds. The outcome for the company? Several workdays are saved for HR specialists every month after major hiring events — all thanks to the efforts of just two analysts, without having to wait in line for development resources.

How to Know If an Idea Is Worth the Effort
Here’s our quick checklist — five questions we ask ourselves before starting to make sure an initiative is truly worth pursuing:
✓ Interest + value: It excites you personally and solves a clear pain point for the team.
✓ No duplication: You’ve checked the dev backlog and nearby initiatives — no one else is already doing it.
✓ Fast prototype: You can build a demo using available APIs or scripts.
✓ Measurable impact: For example, the “minutes per candidate” metric dropped by 60x.
✓ Scalability: The solution can be rolled out to other Avito business units.

What Could Go Wrong and What to Watch Out For

Even a great initiative can run into hidden pitfalls. Here are three common situations to be aware of:

No clear hand-off of responsibility.
If you’ve built a useful tool, it’s crucial to agree in advance on who will maintain it. Otherwise, you may end up stuck in a tech support role. It’s better to involve the process owner early and hand over the solution for ongoing management.

Overlooking security requirements.
Storing logins, passwords, or tokens directly in code or on external servers is a common mistake. This kind of data must be securely protected, and all company security policies should be followed.

Overlapping with other teams.
An analyst’s initiative might touch on areas owned by product or development teams. If someone else is already working on a similar solution, it can lead to duplication or conflict. That’s why it’s important to check early who’s working on what and align responsibilities. This helps avoid misunderstandings and amplifies the impact of the initiative.

Conclusion: How to Start Taking Action

If you want to try stepping outside your immediate area of responsibility, start small. Pick one task per quarter that can be simplified or sped up using data, automation, or just common sense. It doesn’t have to be perfect — an MVP is enough to demonstrate the idea in action.

Build the solution yourself or gather a small team. Measure the impact: how much time, effort, or mistakes you’ve helped reduce. Document the result, create a short guide or write-up. Share it with your team, leadership, or professional community.

Even one successful initiative can make a big difference: make your colleagues’ lives easier, save resources, boost your visibility, and accelerate your career. And if you keep taking initiative regularly, it’s no longer just a good habit — it becomes a real investment in your professional growth.

How to Move from Senior Analyst to Team Lead: A Step-by-Step Guide

Sergo — Wed, 19 Mar 2025 10:23:12 +0000

Every senior analyst eventually considers the next step in their career: should they continue deepening their expertise or explore a managerial role? For many, this decision comes with fears and doubts — after all, not everyone is ready to take on the responsibility of leading a team.

My name is Sergey Medin, and I am the Team Lead of Sales Analytics at Avito Real Estate. In this article, I will share my experience and strategy for growing from a senior analyst to a team lead.

Expert or Managerial: Two Main Career Paths for Analysts

In large companies, analysts typically have two possible career growth paths: managerial or expert. This allows each individual to choose the path that best aligns with their interests and strengths.

It is important to understand that an analyst's career development does not necessarily involve moving into management. Many professionals achieve significant success by continuing to develop as experts, deepening their technical knowledge and skills without taking on leadership responsibilities. In such cases, the expert track becomes an excellent choice.

Companies offer competitive salaries, bonuses, and other incentives for expert analysts, comparable to managerial compensation.

Example of managerial and expert tracks in a company

Career tracks may vary slightly depending on the company. For instance, at our company, senior analysts can choose the expert track and transition to the position of Lead Analyst, focusing on deepening their technical skills. Alternatively, they can follow the managerial path and become a Team Lead if they are interested in leadership tasks.

Key Differences Between a Team Lead and a Senior Analyst

To move from a senior analyst to a team lead, it is essential to understand the key differences in their roles, responsibilities, and required competencies.

1.Role Description

A senior analyst is responsible for analytics within a specific domain. They solve open-ended problems, bringing value to the business. They independently plan their work for the quarter and generate analytical tasks, aligning them with the team lead.
A team lead is responsible for solving complex analytical challenges, establishing effective analytics processes, and facilitating communication within the team. They oversee metrics for an entire unit, draw new ideas from external interactions and industry trends, and implement innovative solutions, even if they do not immediately gain support.

2.Key Responsibilities and Competencies
Senior analysts and team leads have a similar level of technical expertise; however, their roles differ significantly.

A senior analyst does not need to manage a team, allowing them to fully focus on solving complex technical tasks.

These tasks may require applying multiple methods and tools that need to be integrated into a unified analytical system. To achieve this, a senior analyst must have a high level of proficiency with the entire tech stack, which typically includes SQL/DWH, data visualization tools such as Redash/Plotly, statistics, mathematics, Python, and Machine Learning.

Additionally, companies value senior analysts who share their expertise with colleagues and speak at internal meetups.

A team lead spends no more than 50% of their time on technical tasks, with the rest dedicated to management.

They must find an approach for each team member: explain tasks to junior analysts in a way they can understand and work effectively with senior analysts while avoiding excessive pressure, which may not be productive.

Team leads often operate under stress and experience pressure from both sides: from team members expecting support and from leadership demanding results.

Balancing these expectations is one of the key challenges for a leader.
An essential part of a team lead's role is the continuous search for growth opportunities in both the product and business. They analyze current strategies and look for ways to improve them, helping the company maintain its competitive advantage in the market.

Additionally, a team lead actively participates in the hiring process: they justify the need for team expansion, take part in interviews, and support the onboarding of new employees. Like a lead analyst, a team lead also shares their expertise externally, representing the company at industry events.

3.Growth and Development Opportunities

A senior analyst has the opportunity to expand their competencies and develop horizontally by taking on the lead analyst position.

To achieve this, they need to deepen their knowledge of all necessary tools and successfully complete a project that positively impacts the metrics of an entire cluster. Such a specialist serves as a center of expertise, identifying open issues in the product and sharing their knowledge and insights at external events.

One potential risk for a senior analyst is stagnation—the illusion that everything has already been learned and further growth is impossible. In such a situation, it can be beneficial to try mentoring younger specialists, as this not only helps them grow but also stimulates the senior analyst’s own professional development.

Upon reaching the team lead position, professionals can continue progressing toward becoming a division lead.

This role involves coordinating multiple teams, setting long-term goals, and shaping the analytics strategy for an entire business cluster. To move into this role, a team lead must successfully achieve their objectives and develop a comprehensive strategic vision for their domain.

Moving from Senior Analyst to Team Lead: Insights from Personal Experience

When I faced the decision of further career growth, I chose to pursue vertical development and become a team lead. I was drawn not only to technical challenges but also to the opportunity to build processes, establish communication, organize team workflows, and support other analysts in their professional growth.

To transition from a senior analyst to a team lead, there are two main paths:

1.Growth through Initiative and Achievements
For a senior analyst aiming to become a team lead, it is crucial not only to perform their duties successfully but also to demonstrate leadership qualities. This includes actively contributing to the development of the team and the company on a more strategic level.

While senior analysts already play a significant role in business-impacting tasks, the key differentiator is proactive initiative in creating new opportunities. For example, leading a small group (2-3 people) to execute a project that positively influences key business metrics. Another critical factor is mentoring colleagues and sharing expertise, as this demonstrates readiness to manage a team.

In large IT companies, work performance is typically reviewed periodically, and if a senior analyst’s results align with the expectations of a team lead role, they receive a promotion.

2.Growth through Changing Companies
If career growth opportunities are limited at the current employer, another option is to move to a different company for a higher-level position.

I chose the first path. For me, growing through initiative and achievements was the most natural and engaging approach. The company I was working at at the time provided clear opportunities for career advancement.

Key Steps That Helped Me Become a Team Lead

Step 1: Study the Hard and Soft Skills Required for a Team Lead
I thoroughly studied the skill descriptions for analytics team leads available in the company's knowledge base. I also reviewed job postings and spoke with my manager. Together, we created an Individual Development Plan (IDP), outlining my current competencies, strengths, and areas for growth.

Based on this, we identified the skills that required further development and defined specific goals and action steps to help me improve. Among hard skills, I focused particularly on mastering Python libraries at an expert level (pandas, seaborn, requests, etc.), as well as developing the ability to formulate strategies and make independent decisions.

Regarding soft skills, I actively worked on leadership qualities, interacting with junior and mid-level analysts and coordinating their work.

I also paid close attention to motivating the team, effective communication, and conflict management. Platforms like Coursera and Stepik were particularly helpful, as they offer a wide range of courses developed by professionals from top international companies and universities.

Step 2: Understand the Company’s Strategic Business Goals
For a team lead to be successful, they need to understand not only their specific area of work but also the company’s broader strategic goals. I suggested to my manager that we organize regular meetings to analyze results, discuss initiatives, and align on the overall objectives of our department.

This allowed us to identify the current product priorities and helped me understand how I could contribute effectively. Additionally, on my own initiative, I analyzed available reports and company news, which enabled me to propose more efficient solutions and improve the team’s performance.

Step 3: Take on Responsibilities Typical for a Team Lead
One of the company's key challenges was the high cost of courier acquisition. I decided to demonstrate my team lead potential by starting with an in-depth analysis of the processes in this area. My task was to conduct a comprehensive analysis of all acquisition channels, identify ineffective ones, and create analytical dashboards for managers.

This required coordinating the work of multiple teams, delivering presentations, and closely collaborating with colleagues. I also took charge of backlog management, made key decisions independently, and delegated other tasks by identifying the right executors and aligning with them.

As a result, we reduced courier acquisition costs and improved team efficiency, confirming my readiness for a team lead role. This project is just one example of how taking initiative can drive meaningful impact.

Step 4: Prepare Thoroughly for Performance Reviews
A performance review is an evaluation of an employee’s results over a specific period, which can lead to a promotion. The frequency of reviews depends on the company.

During a review, it is crucial to clearly and convincingly present your achievements, supporting them with quantitative data rather than just listing responsibilities. For six months leading up to my review, I collected and documented evidence of my achievements and growth, including successful projects, feedback from colleagues and management, as well as my own observations on my development.

My progress was noticed by my manager even before the review—I was entrusted with hiring new employees for a project. This was a strong indication that I was moving in the right direction.

Final Thoughts

By following these steps, I successfully transitioned to a team lead position and continued developing in the managerial track. Later, I wanted to work on a new product, so I moved to another company.

When choosing a new employer, I focused on companies with a well-structured performance evaluation system. For example, in my current company, career growth is determined through calibration and performance reviews, which take place every six months. During these sessions, team leads and division leads (leaders of team leads) gather to discuss each employee's results and make a collective decision about promotions.

This approach minimizes bias. If a company lacks clear growth opportunities and a structured performance evaluation process, career progression can become unclear. That’s why it’s essential to clarify these aspects during the interview stage.

I hope my experience proves valuable and perhaps inspires you to take the next step in your career.

If you have any questions and would like to discuss career development, feel free to message me on LinkedIn!

How to stop complaining and improve a web service yourself without developer help

Sergo — Mon, 10 Mar 2025 08:48:49 +0000

Hi! My name is Sergo Medin, and I am the Team Lead of Sales Analytics at Avito Real Estate, one of the world's largest classified ad platforms. You may be familiar with the situation when you want to add a new feature to an external web service, but obstacles arise: a complex request process and heavy developer workload.

Sometimes a new feature is needed right now, and there is simply no time to wait. In such cases, there is a great solution—create your own script that will significantly simplify working with any web service. I'm not a developer, but I have basic programming knowledge in JavaScript, which is enough to write such scripts in just a few hours. In this article, I will explain in detail how to do this and provide a step-by-step guide.

Why you don’t always need to wait for developers

The classic approach to development is valuable because new features are well thought out, optimized, and thoroughly tested. This helps create stable and maintainable solutions. However, the main drawback of this approach is that it takes a lot of time. Moreover, development requires deep knowledge and skills, making it inaccessible to most employees.

For me, local improvements that can be made independently are a way to simplify routine tasks. Yes, for fundamental changes, you still need developers' help, but small, useful improvements can be implemented quickly and with minimal costs. Such solutions can save time and effort and increase work efficiency since you no longer have to wait for the much-needed updates.

This approach is used at Amazon

The company encourages employees to solve problems with web services on their own.

The logic is simple: writing a script and sharing it with colleagues is much faster and easier than trying to initiate large-scale changes to an IT product. Yes, this might be a temporary and "crutch" solution (we'll discuss the risks and limitations below), but it requires minimal time and allows you to get the desired result quickly.

How to Improve a Web Service Using the Example of a Recruitment Automation Service

My team is constantly expanding, so I often interact with HR specialists and participate in the hiring process. To automate and speed up this process, Avito recruiters use the Huntflow service. However, during work, they noticed that it was necessary to add several features to speed up the process and eliminate routine tasks.

Since such changes are implemented strictly according to the service's development plan, it can take time. Therefore, to help our recruiters, we decided not to wait for the implementation of changes on Huntflow's side but to quickly create the necessary features using JavaScript scripts for TamperMonkey. This allowed us to significantly reduce the time spent on routine tasks and provided recruiters with a convenient and flexible tool for work.

Let's look at a couple of problems HR specialists face as an example:

Problem #1: Manually exporting information from Huntflow to an Excel file.
To compile a table with candidate information, recruiters need to manually copy data such as email, phone number, full name, Telegram nickname, job title, and other information from Huntflow. This process is repeated for dozens, sometimes hundreds, of candidates—manually filling out an Excel file can take hours. At the same time, standard data exports from Huntflow do not allow exporting everything needed.

Solution: I wrote a script that automatically navigates from one candidate to another, collects the necessary information, and creates an Excel file at the end. This frees up HR specialists' time for more important tasks instead of performing routine work.

Important Note: This solution cannot be called fundamental.
Yes, Huntflow has an API that allows you to implement automatic data export, but it requires more time and resources. In situations where a quick solution is needed, TamperMonkey scripts are the perfect option, as writing them takes only 1-2 hours.

If a higher-quality solution is needed, then you can initiate processes to improve web services by developers, while already having a temporary solution based on scripts. This way, we immediately gain time and can calmly wait for a full-fledged update.

Problem #2: Processing responses takes a lot of time because candidates often apply for several positions.
Suppose a person responded to a sales position at Avito Auto and a similar one at Avito Real Estate. The Huntflow interface is designed so that the HR specialist needs to manually click through each job for this candidate and set a status, for example, "candidate transferred to another job." These routine actions take time, especially if the company has many vacancies, each with dozens of applicants.

Solution: I wrote a script that creates several additional buttons. They can be selected depending on the goal, for example, to continue working with the candidate or not. The HR specialist presses one button, and the script literally sets the required statuses for each candidate in just a few seconds. This greatly speeds up the work.

HR specialists were very pleased with this solution. Here is what they say:

Previously, we manually exported candidates to a table because there was no automatic export of contacts (Telegram, LinkedIn). With the new button, the task is solved much faster and requires minimal involvement. When our team needed to invite 200 candidates to an event and fill in a table with their contacts, we thought it would take a lot of time. But it happened that on the same day we got a script, which we immediately tested, and the export took just a few minutes.

Anastasia Bashkirova, Senior Recruiter at Avito

Thanks to the script, we now quickly process responses, can instantly transfer a candidate to work, or reject a resume in one click.
The coolest thing is that the automation of routine tasks is now in our hands—and we have plenty of ideas for further improvements!

Emilia Ashanina, Researcher at Avito

How we organized script distribution

We placed them in a special GitHub repository, and all Avito managers can copy the scripts from there. If the script is updated on GitHub, it automatically reaches HR specialists through the TamperMonkey update system.

How to Do It Yourself (Without Technical Details)

The idea is simple: write or find a suitable JavaScript script and run it in your browser. The script will modify the loaded page and add everything you need to it. Here's how to do it:

1.Install a Browser Extension: You need an extension that allows you to create, edit, and run scripts. There are several options, but I use the free Tampermonkey extension. It works with Chrome, Microsoft Edge, Safari, Opera Next, and Firefox.

👉 Download and Install Tampermonkey

2.Browser Restrictions: Your browser might block running JavaScript by default to prevent malicious code from executing. Therefore, only use code from trusted sources and grant the extension the necessary permissions to run JavaScript.

3.Add the Required Script to the Extension: An important note: writing code yourself is not mandatory. You can find something suitable in an open library. For example, there are many useful scripts on the Greasy Fork website. It's one of the largest resources for finding scripts, offering a vast collection of vetted community-created scripts. You can find almost anything, from ad blockers to enhancements for various websites.

📂 Explore My Repository for Huntflow Scripts

4.Install Scripts in a Few Clicks: If you use Huntflow and already have the Tampermonkey extension installed, just follow one of the links below:

You can view the source code and, if desired, install the script by clicking the appropriate button:

Test the Scripts in Huntflow: Once installed, you can try using the scripts in Huntflow (if you have access to this service, of course).

If you decide to write the script yourself, here's how the code works. I'll use an example of a script that adds a button to the page and collects data from candidate profiles, exporting them to Excel:
1.Script Metadata: At the top of the code, the script's metadata is defined—this part is usually straightforward and doesn't need much explanation.
2.Finding the Right Place on the Page: The next part of the code searches for the spot on the page where our new element (e.g., a button) will be added. In this example, we are looking for a container on the page where the button for exporting data will be placed.

This is done using the document.querySelector method, which allows you to find HTML elements by a specified CSS selector.

var buttonContainer = document.querySelector('div.search--qvPi4.item--R7wgx');

You can find the right container on your page using your browser's developer tools.

3.Next, the code describes adding a new element to the page: once we find the right container, a new div element is created, inside which a button with the text "to Excel" will be placed. This button is then added to the container found in the previous step.

var newButton = document.createElement('div');
newButton.className = 'item--OBfF8';
newButton.innerHTML = '<a><span style="padding: 5px; border: 1px solid #ccc; border-radius: 3px; cursor: pointer;">to Excel</span></a>';

4.Next, the code responds to user interaction with the new element: here, we add a click event handler to the button. When the user clicks the button, the data collection process starts. In this example, all elements on the page containing candidate data are searched, and the data loading process begins.

newButton.querySelector('a').addEventListener('click', async function() {
    console.log('HF_SE: Button clicked');
    var applicantRootElements = document.querySelectorAll('div[data-qa="applicant_root"]');
    // Logic for processing the found elements and exporting data
    // ...
});

5.The script is completed by the code responsible for collecting, processing, and saving data: once the data is loaded, it is processed and saved in Excel format. Using the xlsx library, the script creates a new Excel file and writes all the collected data into it.

function generateExcel(data) {
    var ws = XLSX.utils.json_to_sheet(data);
    var wb = XLSX.utils.book_new();
    XLSX.utils.book_append_sheet(wb, ws, "Sheet1");
    XLSX.writeFile(wb, "data.xlsx");
    console.log('HF_SE: Excel file generated');
}

Disadvantages of TamperMonkey Scripts

Despite all the advantages of using TamperMonkey scripts, it is important to consider the following limitations:
1.Scalability and Maintenance Challenges: For your script to work for other users, they all need to install the TamperMonkey extension and manually add the script.
2.Dependency on Web Page Design: Scripts interact with specific elements on the web page. If developers change the structure or appearance of the site, the script may stop working. This requires regular monitoring and updating of scripts in case of site changes.

Conclusion

TamperMonkey scripts are a powerful tool for automating tasks in the browser. They can significantly simplify working with web services by adding the necessary features or automating routine actions without waiting for updates to the services themselves. However, you should also consider the drawbacks, such as the need to adapt scripts in case of changes to the target web pages.

At Avito, we actively use such scripts to quickly solve tasks that employees face. This allows us to respond quickly to requests and launch temporary solutions while more large-scale improvements are in progress.
Especially when it comes to improvements to external services like Huntflow. This approach allows us to effectively achieve results. Try it, experiment, and share your experiences in the comments!

P.S. If you are interested in exchanging experiences, gaining new knowledge in analytics, preparing for interviews, and building a great career—I look forward to seeing you at personal meetings. I act as a mentor for specialists of different levels: from juniors to team leads. You can find me on LinkedIn, and I will be glad to connect with you!