In today’s data and technology-driven economy, data science continues to rise as one of the most in-demand career paths in technology. Data scientists are analytical experts who extract meaning from data and interpret it to solve complex problems. A data scientist uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge.
Data scientists translate the results they get from analysis into actionable plans and communicate their findings to their organizations. Data scientists can work in various industries and environments, including tech startups, healthcare, manufacturing, and research institutions.
Education
To get started in data science, a bachelor’s degree in data science, business, economics, statistics, math, information technology, computer science or a related field can help you gain the relevant knowledge required to kickstart your data career. From these programs, you’ll learn how to analyze data, and use numbers, systems, and tools to solve problems.
But if your bachelor’s degree is in the arts or humanities, don’t worry. Your ability to think critically and creatively is not lost in a data science career. If you don’t have a degree at all, there are several options for you too. You can enroll into an online course or professional certificate.
Pursuing data science bootcamps also gives you plenty of options to pivot and gain the necessary skills for a data science career. Some bootcamps are in-person over a few weeks or months with a cohort, while others are completed online or at your own pace.
Skills
Technical skills
1. Programming - Programming languages, such as SQL, Python or R, are necessary for data scientists to sort, analyze, and manage big data.
2. Statistics and probability - In order to write high quality machine learning models and algorithms, data scientists need to learn statistics and probability.
3. Data wrangling and database management - Data wrangling is the process of cleaning and organizing complex data sets to make them easier to access and analyze. You’re also expected to have skills in database management since you will extract data from different sources and transform it into a suitable format for query and analysis, and then load it into a data warehouse system.
4. Machine learning and deep learning - Incorporating machine learning and deep learning helps you improve as a data scientist because you’ll be able to gather and synthesize data more efficiently, while also predicting the outcomes of future data sets.
5. Data visualization - Being able to create charts and graphs is important to being a data scientist. With strong visualization skills, you can present your work to stakeholders so that the data tells a compelling story of the business insights.
6. Cloud computing - As a data scientist, you'll most likely need to use cloud computing tools that help you analyze and visualize data that are stored in cloud platforms.
Interpersonal skills
1.Active listening
2.Effective communication skills
3.Sharing feedback
4.Attention to detail
5.Leadership
6.Public speaking
Job searching
Networking is a great way to find data science jobs, especially ones that are related to the industry and niche that you want to work in. By connecting with the right people and companies, you can find opportunities closely related to your interests and future career goals.
Job listing sites are some of the first resources you think of for finding a job in any industry. However, since these are the first places most people go, they are very popular, competition is high, and the boards can often be saturated with listings of mixed quality.
Conferences and other in-person events are ideal networking opportunities. Be sure to treat both people and businesses as equal opportunities. You may meet an incredible manager at a company that doesn’t particularly interest you.
Joining a private or public community forum of data scientists is a great way to network and find jobs. Share your experiences, research, publications, and challenge each other to gain inspiration and fresh ideas.
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