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Oct 21, 2018
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Career Considerations With STEM

I could use some career advice. I’m a recent college graduate working as a database developer for an automobile producer. The job pays well and I have decent benefits, but I work almost sixty hours a week, and I’m already getting burned out.

 

My parents are pressuring me to stay the course, but my brother suggested that I at least explore other careers. And that’s why I need some guidance. My bachelor’s degree is in computer science, and I had a minor concentration in applied statistics.

 

Ideally, I’m trying to target a career that would let me continue using my college education and possibly even incorporate some statistics. Any insight would be much appreciated.

 

It sounds like you’re in the same situation as countless other college graduates around the US. Choosing your career path is no trivial exercise, and it’s likely to have a disproportionate impact on your life. That’s why it’s essential to approach the situation with a realistic mindset. Melanie Pinola at Lifehacker can help you with some of the rote basics. She published an informative article explaining ten tactics to find your career path. You might consider some of her suggestions irrelevant (e.g., “think about what excites you” and “trying an internship”) but there are certainly others that you ought to seriously contemplate (e.g., “finding a mentor” and “making a career plan”).

 

Fortunately, you have some very promising options to entertain. Database development might be a lucrative choice, but if you don’t find it compelling, then it probably isn’t the right fit. However, a computer science degree coupled with a passion for statistics lends itself very easily to data science. Forbes contributor, Gil Press, explains as much in the opening clause of his brief history of data science. According to him, the origins of data science can be traced back to 1962. In other words, the discipline has some considerably well-established roots.

 

Flash-forward to October 2012 and data scientist was declared “the sexiest job of the 21st century” by Thomas Davenport and D.J. Patil at the Harvard Business Review. Why? Try identifying a business, government, or community that couldn’t benefit from harnessing data insights. We’ve entered an age in which data informs an increasingly large proportion of decisions — ones that have a material impact on daily life. That’s why data science is often a thrilling and rewarding career path.

 

Roger Huang at Springboard has already done you the favor of outlining different data science career paths. He offers several salient industry examples and even includes other key information such as average salaries and sample job posts. Those should serve as decent starting points, but you’ll want to also explore real job postings for data scientists. You could discover that having an advanced degree is a meaningful barrier. That’s been the case for multiple Science, Technology, Engineering, and Mathematics (STEM) fields. Forbes contributor, Bruce Kasanoff, describes how a master’s degree is the new bachelor’s degree for some of the most competitive STEM fields.

 

The good news is the same relentless progression of technology that has made data science such a lucrative career choice has also made higher education more accessible than ever. In other words, you don’t have to drop everything and relocate your whole life simply to advance your education and professional career. You can definitely find an online data science degree program that fits your selection criteria. The most important thing, however, is ensuring that you fully appreciate the difference between an undergraduate and graduate STEM education.

 

Raymond Lutzky, Ph.D., at CollegeXpress put together a thoughtful overview that highlights four major differences between your undergraduate and graduate STEM experience. He explains how faculty and administrators serve as gatekeepers at the graduate level rather than the university admissions office, which is exclusively responsible for the undergraduate students. Understanding the rules of research is another key takeaway presented by Raymond.

 

All this being said, you should also realize that other options exist that could prove to be equally appealing. Another Forbes contributor, Meta Brown, took the initiative and introduced ten careers related to data science. Examples range from economists and epidemiologists to meteorologists and quantitative analysts. All of them could be viable paths, too, depending on the outcome you desire. Either way, you shouldn’t disqualify any options until you learn more about them from those occupying the positions.

 

“The most common way people give up their power is by thinking they don’t have any.”  — Alice Walker

 

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