Douglas Mason [Data Scientist at Twitter] – “What I carried with me…was a relentless enthusiasm. I’m certain that was key to my success, leading to my current role as a Data Scientist at Twitter”
Last week, I helped an incredible person find her first commercial role as a Data Scientist. No, the lovely lady above isn’t her but what I imagine her expression to have been when she got the role. Anyway, she has a PhD in Astrophysics along with 2 years’ of post-doctoral research experience from some of the top universities in the world. But it still wasn’t an easy ride to becoming a Data Scientist.
There are many routes to take to become a Data Scientist so I want to outline the problems you may face when transitioning your career to Data Science, from Science, and how best to tackle them.
PhD’s supply many valuable, transferrable skills. If you have just completed a scientific/quantitative PhD, your last 3 years’ should have included:
- Research involving programming and large datasets
- Stubbornly persisting when asking / answering hard questions
- Constantly explaining the motivations and reasoning behind your work, and perform numerous presentations.
This is what a Data Scientist does day in day out. So, when it comes to your interview, you need to show how what you’ve learnt in academia is helpful for a business and its problems.
A PhD doesn’t necessarily help your CV stand out from the crowd as there are a lot of PhD graduates applying for Data Scientist positions right now. What you need to do is prove that you want to be a Data Scientist in the commercial world. Here’s some things I would suggest:
- Sign up to Kaggle (kaggle.com) and complete a project
- Engage with a Data Science community. For example, if you’re based in London sign up to meetup.com and search for all Data Science related events. Build an idea of what it is to actually be a commercial Data Scientist, discover the ‘etiquette’ and day-to-day normalities of the industry, and even discuss some ideas with fellow event goers. This will provide you with discussion points and ideas in your interviews.
- Were you using MatLab, Fortran, Stata etc. during your PhD? Then it’s time to self-learn Python (http://www.learnpython.org/) and R (https://www.coursera.org/course/rprog). These are the 2 most sought after hard skills for Data Scientist hires.
- Sign yourself up to any related courses or Summer Schools. That PhD graduate I placed last week did the S2DS course (s2ds.org) last summer!
These all prove that you are driven, determined and able to be out of your comfort zone.
Final tip. Apply to the right companies. Many companies looking for Data Scientists either don’t know what Data Science is or don’t need it (or both!). Think about what size company you want to work for, what problems you want to solve and the data sets you want to work with. Perhaps this point should be my next blog…
As always, if you want to discuss Data Science careers with me, Joe Burridge, email me on joe.burridge@welovesalt.com or call me on +44(0)2079 282 525.
Sources:
- http://insightdatascience.com/blog/from-phd-to-data-scientist.html
- http://www.quora.com/Do-I-need-a-Masters-PhD-to-become-a-data-scientist
- http://www.quora.com/How-do-I-become-a-data-scientist-without-a-PhD
Joe Burridge 