#108 RE-RUN: SHOULD I BECOME MORE TECHNICAL OR BUSINESS FOCUSED IN MY DATA SCIENCE CAREER?

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By Felipe Flores. Discovered by Player FM and our community — copyright is owned by the publisher, not Player FM, and audio is streamed directly from their servers. Hit the Subscribe button to track updates in Player FM, or paste the feed URL into other podcast apps.

If you are trying to choose what skills you should build as part of your career, no single answer fits everyone. It depends on your strengths and ambitions. Your strengths are the things you are naturally good at. If you're not sure what your strengths are, then think about the things that people come and ask you about. When someone asks you how you do something, most likely that is one of your strengths.

Also, think about where you want to end up in your career. For instance, if you're going to become a manager, find a way to be a leader on a project and develop your soft influence. Hard influence is something that comes from authority. Whereas soft influence is something that we can build upon. Find a way to lead a project among your peers. Taking the lead will allow you to practice your influence, leadership, and management skills. A group of people will follow the person with an organized and well-thought-out plan; be that person!

Another tip - do not be the person that blindly follows what they enjoy; it's not a strategic way to go about crafting your career. Felipe has seen people have a successful career doing work that they enjoy. However, they will eventually lose their love for it. Plus, if you only follow what you enjoy, then you run the risk of getting pigeonholed in an area that may not have future growth. Also, it might be an area that loses demand and importance; it can make your skills irrelevant.

At the end of the day, we need generalists. Companies need people who are knowledgeable in the end to end process. As an industry, data scientists are in high demand. Plus, they need people who have a mix of skills. There are always more roles being added because the industry is starting to understand that a great deal of knowledge is required to build a successful data science team.

Enjoy the show!

Read the full episode summary here: Ep 108

Thank you to our sponsor, Talent Insights Group.

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