DEV Community: Sia

Thank Your Angels 2: The PowerPuff Girls

Sia — Mon, 10 Aug 2020 23:13:45 +0000

Hellooooooo!
Feeling a little like Robin Williams in Mrs. Doubtfire today, but I digress.

The first iteration of this post was a happy meltdown after some Twitter warriors helped me gain eyes to land job opportunities. Not much has happened on that front, but here is (to me) the wildest thing that will ever happen over tweets. And before you read this as a lesson in how not to write about a tech post, this is a tech networking post, so no code snippets here. Sorry!

The intent is to share with you a list of some awesome people who you can connect with for free through a series of anecdotes. It is meant to celebrate my tech anchors in life's ocean (Don Williams anyone?). I hope to tell you about them extensively on a weekly basis. If I have now lost you, happy Monday. Also, enjoy Poison because today is Michael Bivins' birthday!

Moving on...

In the last month, I have connected with some amazing people in technology and specifically, data science. This all started because I was minding my business and posting I don't know what about the WNBA OK? That's how the PowerPuff Girls of data happened. First, @dikayodata liked the tweet and followed. Now if you have not connected with this lady and her empire, it includes a podcast, a newsletter, and Twitter chats that combine felines and data. Perplexed by this connection, I went and read about her (as one does), followed and subscribed to everything before thanking her because what luck! And then this offer (which I double-checked) happened!

DiKayo Data

@dikayodata

Omg there’s SO much sports data out there begging for you to analyze it so that’s awesome. I haven’t talked about that on #DataFemme at all. I’d love to pilot that with you as long as @thedariaedits joins because I do not know near enough about sports.......... twitter.com/siawayforward/…

01:19 AM - 12 Jul 2020

Sia Seko 🇹🇿 @siawayforward
@dikayodata Can't wait!! And I am a data baby. Only worked as an analyst in relocation for ~3 years before, but sports would be my dream hence all the WNBA tweets and side projects😂😂

0 0

It was magical, made my week, and I very much look forward to it.

The second PowerPuff girl, Alise, was actually mentioned to a group of us who attended @Latesha_Byrd's black ceiling talk days earlier. As a member of Latesha's (now try keeping the names straight) Career Chasers club, Alise has now secured the bag and is a Sr. Analytics Engineer at Netflix! Last but certainly not least, the one and only @DataSciBae - I had already been following! But guess what had happened right before that Dikayo Data madness?!

Weeks earlier, Ayodele had expressed interest in taking on a junior data person a.k.a. a data baby, to help with a project she is working on. I had signed up for this and continued along while applying for jobs before our Cinderella moment is over with the USCIS and ICE (because immigration). Meanwhile, Alise had also posted a tweet expressing willingness to hold calls with any data babies who had questions and I had signed up for that too.

Now let's fast-forward (back) to that moment when I decide to start listening to #DataFemme, the Dikayo Data podcast, minutes after subscribing. The first episode had (you guessed it) all three of these women talking about race, bias, and data science. They all know each other! What triple luck and joy. Needless to say, I went back to Twitter to thank all of them for connecting me to each other in this serendipitous moment and being part of the daily newspaper that is my Twitter feed.

So today, I'd like to thank them for existing and giving. When I open Twitter, it is so refreshing to see the duality of all these women. They have each either given me or presented me with an opportunity to improve my job chances, taught me about what is important while learning about data science, and lived loudly enough to deafen all those who say they should be quiet. Not to mention, having e-nteracted with the PPG has led me to e-meet some more amazing women in tech and data; to be featured in this small deverse series (get it?) in the next installment of Thank your Angels!

How to Data Science Pt.1 Starter Kit

Sia — Thu, 09 Jul 2020 22:38:38 +0000

Hi all,

As a fellow job-seeker, I write this humbly and with the intent of helping others build up and bridge their own gaps in trying to enter this field. Most of this post is just a consolidation of tips and sources from data scientists and educators that have helped me along the way. Though not successful myself in the immediate goal of employment, I am hopeful that at least one person will get started or improve on something towards this collective goal.

Step 1: Coding Language & Editor:

In the last few years, Python has overtaken R and others to take the crown of the language to learn should you want to enter this field. FreeCodeCamp has an extensive collection of certifications that are suited towards beginners. This four hour course for an absolute beginner is great. You have explanations, and step by step live practice as you move along where you can track your progress. The site has a data analysis, machine learning, and more tracks that go over the materials beyond the basics, but more on solidifying that below!

Now the editor: This comes second because freeCodeCamp has a hands-on approach, so you are able to code while learning on Scrimba, their platform of choice. You will however start delving in, and want something for yourself! Code needs a home too.
If you are a beginner, Anaconda works best because it comes with the main preinstalled packages, Python dependencies built in, and a way to add notes as you learn in a formatted manner with Jupyter Notebooks. You can choose to transition to other editors, so please do not let the above statement be gospel if you do not enjoy using Anaconda with Jupyter Notebooks long term. I transitioned to Visual Studio Code because of the centrality and simplicity of the tool. However, you will be installing a lot more packages by yourself.

Step 1a: Underlying Theory -> Statistics!

Yes. At least for the basics of machine learning, you will need to have a little bit of foundation underlying your practice. Coding is just a way to help you apply theory to solve decision-driven data problems. You need to be able to know how and what you are evaluating in the raw data in order to be able to extract information from it. A great book, first recommended by @DataSciBae on Twitter, is O'Reilly's Practical Statistics. As a math degree holder, I found it was effective in pointing out the direction of focus so that one can work on improving and understanding those particular concepts in theoretical and applied mathematics in order to use and properly practice ML techniques. Get the 2nd edition that has both R and Python examples. See below for the thread and her advice. Also consider following her for more!!
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Even more basic is an understanding of probability and statistics. If this book does not spell it out too clearly for you, consider taking Khan Academy's Statistics and Probability course

Step 2: Big Data and Business Intelligence

At this point you will have some basics of the landscape, but there's more! Think of this point as having laid down the foundation cement on your home (where I come from we build homes with bricks and cement only, but this is a story for another day). Now we add bricks! The meat of data science is going to be lost if you don't know how to handle data. Understanding concepts such as data cleaning, exploratory analysis, and also data mining (because it does not magically appear!) is important. UC Davis has a Coursera specialization to fit this need. It is also suited for beginners, and will guide you through querying, SQL (structured querying language), and Apache Spark among other tools and skills.

Step 3: Dig Deeper -> What did you like?

So if you have gotten this far, you would understand how to mine, clean, query, and visualize data, how to create models and explore data for insights, and of course, you are a Pythonista (R people, don't kill me)! So now what?
There are so many roads, reader. Each of the above items mentioned are jobs in and of themselves. If you are a fan of data collection and visualization, you could be a data analyst. If the process of acquiring and preparing data to be used by others appeals to you more, then you are somewhere between a database administrator (governance) and a data engineer. What about just the models? The only things you care about are normalizing data and building the best model in the world (which spoiler alert, you should know doesn't exist) and communicate these insights to stakeholders. Well then hello, data scientist! You want more? Get to combining all of these skill sets and some software engineering ones to become a machine learning engineer then (which is a land mine by itself and one I intend to enter)!

So all that blabbing and diddly daddle above didn't really guide you towards anything specific because like Nelly Furtado said, the more you know, the less you know.

At this point, you have to make a decision about which direction you want to go. After you do that, come back because we are going to take a deep dive into resources that would enhance any one of those jobs above (also because I have to finish putting those together ha!). Each track has more tools and specialization to focus on. Also note, the data scientist has multiple directions into which they could veer. We'll get into those too in the next (or next next) article of this series.

Until then, enjoy Nelly's music (¡Tambien en Espanol aqui!) and this is 1/?

Sia

Thank your Angels & Be a Nice Human

Sia — Tue, 23 Jun 2020 03:42:20 +0000

This post is not about anything tech related. Today was a crazy roller-coaster of a day. It started with high energy and the intention to finish my Twitter bot to remind the world about the angels we lost, specifically Breonna Taylor. Twitter said no for now, but trust and believe, we are going to get people to see her life as a person, not the person who died. She had dreams and ambitions and should be remembered as such.

Ok this is not an activism post either, it wasn't a trap. Just that Breonna's life meant something. So I read Twitter's email, respond and get back to testing the parts I can without access to the API. After failing twice at one method, the brain and I take a break and that is when we see the news about H-1B visas.

You see, not only am I an aspiring data scientist. This is my tourist country - where some have trekked for the promise of a better future. And you know before COVID-19, the job search was hard. It started in October 2019. It is hard to get a job in tech, now add being an immigrant in this country. Don't get me wrong. I understand that you look out for the citizens first, and that this is so good and therefore not easy to get into. It is admirable that locals too get to wish for this promise of a better life. Who wouldn't want it? Anyway..

So the news - the executive order heard round the world. The one that extends the freeze on H-1B, H4, L and a couple of other visa classes to foreign skilled workers through the end of 2020. The end of the year. Six months in which high tech, health informatics, medical professionals (you know, the thing we all need to be alive right now) are restricted from coming to work in the U.S. to allow for local workers from the gaudy unemployed group (of which I am a subscriber of) to thrive. This news did it for me because just go read about it... This is not an immigration post either!

So I went on Twitter, posted a chain selling my (very junior and still developing) skills to anyone who would listen for anything! I even said pay me $0 just as long as there is no deportation. Sidebar: students have an OPT option which is the kid of the H-1B. So if one is frozen, you know the other one is next (no proof whatsoever, but listen to the speeches, OK). And we have to renew STEM OPT so who knows if we can next year? Need-not-less to say, desperation time OK? Then I went on LinkedIn and sold myself for nothing again. What followed is why this prose is happening right now.

First, a direct message from a lovely data scientist lady with a suggestion to tag people along with links to helpful tools to help me grow and sharpen my skills. Took this advice because YES. Other women have more exposure and a tag for retweet adds eyes. Listen to your (professional) elders people! Next came a lovely lady who would love to talk to me about joining a bridge program that would allow for placements; and even though it is a post-doctoral program, "don't worry about the PhD, we can move forward without it"!. Isn't that two angels in a row or what? As the retweets and likes were coming in, my friend told me that her and her infant son are praying for me, and to come to Canada - also sound advice but then again, COVID-19 != travel plans.

Then Sarah happened.

In a past life, I worked in global compensation and finance - calculating cost projections, tax payments, cost of living adjustments and allowance, making balance sheets, you name it. A lot of math stuff that was fun but with excel (don't laugh, accounting jobs love it but I made macros!). Anyway at this job, the first person not on my team that ever talked to me was Sarah. She had started six months earlier, the nicest smile you will ever see, and always checked in on me when we ran into each other. Not "how are you, fine" checked-on-me, checked-on-me checked-on-me. I even left her a thank you note when I left that job because she had made that much of an impression on me in my time there.

So here I am, just poured my heart out on LinkedIn and what does this woman do? She re-posts the post and asks her network if they could "check out my friend Sia" for data analyst, data scientist, tech-writer, writer (I have a writing degree and use it always, even published in English-y things but I digress) positions. Sarah and I had not spoken in years, but this woman remembered me and said the kindest things to me as we went back and forth on messages while I cried. Not only does she do this, she sends me to her employer's job site and her email, and tells me to pick positions so she can start floating this resume out like dollar bills in that place we shouldn't be in right now because COVID-19. Ha!

Anyway, miss thing then gets me to another company's site and tells me to go through those jobs and research them because she knows a recruiter there. Now at this point, you might think I am just going off on a random day talking about one-self but why did Sarah remember me and re-post this? And give me all her resources under the sun? She thought I deserved it. She had more to give than I had left to fight with, and she picked me back up with my crying self and just did the thing. Now exit if you don't pray before I continue because...

...I pray that we can all be Sarah to someone. I don't know what it was I did for her, but she is just the best human is my answer - as good as I remember from two years ago. She wasn't on my team at work, not even the same department, not even the same floor! Sarah and I saw each other every other month or so, but the interactions were packed with love and just joyful exchanges. So all of this to say, WOW. And be nice to people. It doesn't cost you anything and you might be saving a life. I don't know if this leads to anything, but it does not matter. Miss Sarah was my third and most charming angel of the day and she gave me perspective in this sinking ship of a year. That Andy Dufresne kind of hope that you have to keep staying alive for.

So for anyone out there struggling with a project, a job application, tech interview prep, waking up in the morning, I am rooting for you and praying for you. If there is anything I can give you, please ask. Hope, a cheer, an edit (did I mention I edited a nationally recognized collegiate journal when I was an undergrad?), let me know. And to all the angels out there, thank you for the advice, the retweets and likes, the kind ear, the loving encouragement, and the infusion of hope that this year is not all lost and that we all deserve nice things. Blessings to you and yours, Sarah and your fellow angels!

With love,
A Shawshank Redemption fan.
(if you don't know this movie, watch it before you die. You're welcome)

JuneteenthConf 2020

Sia — Fri, 19 Jun 2020 21:28:28 +0000

Hey y'all. JuneteenthConf is wrapping up with today's last talk. Please drop by tomorrow, some inspiring and great Black leaders in tech. Live free streaming here
https://juneteenthconf.com/