Looking to Make a Career Change in this Competitive Data Science Market?

Career change continues to be a hot topic in 2022. Early on in someone’s career, the most important thing is to gather as many skills as possible. For analytics professionals, this will allow you to have a broad sense, overall, of data science and analytics in different industries and organizations, and it will also help you understand what you really enjoy.

Here are some insights that early career data scientists should keep in mind when considering a possible change.

Prioritize advancement. Ensure your next move will further your career in a variety of ways. When changing jobs, it is imperative that you realize the benefits that come with the new opportunity.

Managing your data science career is a balancing act that requires spotting the right opportunities from both a mentorship and management point of view. If you’re still in the first few years of your career, having the opportunity to connect with senior team members and forming valuable relationships can enable both personal and professional growth. Any management experience gained on the job can also enhance your skillset and propel future advancement.

Staying up to date. Keeping well versed in a variety of coding languages can really build a competitive advantage for an early career data scientist. From my own conversations with companies, Python is still a top pick, but SQL and R are also very commonly used. In addition, strong visualization skills (Tableau, Power BI, etc.) are highly requested.

Flexibility. Hybrid and remote work models are becoming commonplace for data science professionals. With this comes added flexibility for each professional to better manage their time.

Oftentimes, data science professionals will choose to go into the office to collaborate and gain team support. While this can be done from home, it is all about personal preference. Explore what works best for you and find an opportunity that supports your unique needs.

Mentorship. As mentioned, mentorship is an invaluable aspect that fuels early career growth. The ability to mentor junior-level data scientists can be a huge growth opportunity for any professional; it is a wonderful way to share knowledge and give guidance while expanding your professional network.

Salary research. Ensure that you are doing your homework on competitive salaries when considering a career change.

Burtch Works publishes an annual Salary Study that focuses on a variety of market trends, insights and research. Be sure to give it a read if you are interested in salaries examined by job level as well as an in-depth demographic analysis that focuses on education, gender and years of experience.

It’s important to keep in mind that base salary is only one level in a good strategy, and there are many other factors to consider before exploring a new opportunity. Benefits, culture, leadership, advancement path, and other factors all play into a data scientist’s job satisfaction.

Understand counteroffers. I recommend that early career data scientists think carefully when considering a counteroffer. Revisit the real reason behind why you explored the market and be sure you will feel confident in your decision when any uncertainty settles down. Recently, I have seen a very high prevalence of counteroffers and I am genuinely curious to see if this trend will continue in the future.

Be sure to weigh all the pros and cons when considering the next shift in your career. Navigating the current job market can quickly become a challenge for data scientists and we are here to help!