What do you need to do to get an entry level job in data science?
This article is written for anyone who is considering becoming a data scientist. That includes young people just starting their bachelor’s degrees and folks in the first two or three years of their careers who want to make the switch.
It’s not for folks who know they are going to pursue one of the new Master’s in Data Science or Ph.D. candidates. It’s for folks looking for entry level jobs that are specifically on the data science career ladder.
Is There a Data Science Career Progression That Doesn’t Require an Advanced Degree?
Yes there is. Like many high skill professions that’s not to say that an advanced degree won’t make it easier but there are definitely ways to enter this market with only a bachelor’s degree.
If you’ve been practicing data science for more than five or ten years you also know that the majority of us over 35 don’t have specific data science degrees. We came to data science via a variety of related disciplines and gained our cred largely based on performance and experience. It’s only the cohort under 35 working in data science that’s likely to have a DS-specific degree, advanced or bachelor’s.
The flack this article is likely to draw is not over the level of degree required or the types of experience but the just-below-boiling controversy about who gets to call themselves a data scientist. The problem in our profession, and I’m not going to solve it here, is there is not an accepted nomenclature that differentiates the various skill levels of data scientists or who gets to wear that title at all.
Employers aren’t helping since actual data science jobs may be called engineer, analyst, developer, team lead or many other less exciting sounding titles.
Other employers are giving data science titles to folks who are not really doing data science, but more descriptive analytics and straight EDW work.
So for simplicity’s sake I’m going to call our target audience folks who are seeking positions as Junior or Associate Data Scientists. Specifically that means doing work that involves detecting signals in the data that can be used to make predictions about future behavior. Not simple descriptive historical analysis of what’s happened in the past.
For Beginners What Does the Market Look Like and What Type of Work Will You Do?
There are two key points to understand here. The first is that the data science market has divided into two distinctly different segments, Production and Development.
Production: This is by far the largest and most mature segment where predictive analytics has been used for longest and where it is best integrated to create truly data-driven businesses. Large B2C service businesses dominate this group, specifically insurance, financial services, cable and telecos, healthcare, plus retail, eCommerce, and some manufacturing. These companies are widely distributed geographically so you can work pretty much anywhere. The primary data science activities are predictive analytics and recommends.