In 2012, the Harvard Business Review declared “data scientist”as the “sexiest job of the 21st century”. Since then, the role has become a major “must” for companies in every business sector, and job growth continues to skyrocket. The title garners hype and high salaries, but just what goes into being a data scientist?
What kind of background does a data scientist usually have?
Among the speakers, no one had the same experience before joining the data science field. Between a biology major who got his Masters in statistics, a neuroscience PhD with a focus on machine learning and a one-time analytics consultant, it was clear that one can make the leap the data science from all sort of backgrounds. The panelists did mention that no matter your previous experience, it’s crucial to be the type of person who excels at problem-solving, who knows how to ask the right question to get a useful answer and who is always curious.
Why do you love your job?
The panelists had a variety of answers to this questions, some of which included:
- You can solve problems that might take others a few weeks in a few minutes
- You’re a part of data innovations that are changing the way the world works
- You can use data to change the direction of an organization for the better, and to inform key decisions
- You get to work with every single department to help optimize products and results
- You never have the same day twice
- You get to work on challenging problems and try to come up with creative solutions
If you can’t get enough of collaborating and want to work in an environment that constantly challenges you, data science might be the perfect fit.
Why do you think data science is so hyped right now, and is the hype justified?
The consensus here seemed to be that because data itself is hugely important, having people who understand how to work with and evaluate it is also vital.
However, the panel warned that the term “data scientist” is so general that it’s mostly lost its meaning; Now, companies want someone with a data skillset who also specializes in machine learning, web development, statistics, etc.
What are your tips for someone weighing grad school vs. tech bootcamp to enter the field?
The first thing the panelists agreed on was that no matter how you learn, having a mentor is imperative to your success. Overall, they favored the bootcamp approach, given that it take less time, less money and will likely have you working with more advanced, up-to-date technology than a traditional grad school would.
They also suggested that before you spend money on higher education or a short-term immersive, you try to teach yourself as much as possible to see if you enjoy data science fundamentals. If you do, onward!
Galvanize offers a 12-week Data Science immersive program. Our students learn and practice essential skills, gain practical experience with projects, and benefit from customized career guidance once the program is complete.