by adamgamble on 4/7/17, 3:27 AM with 1 comments
We aren't even sure where to start when describing the qualifications of a great data scientist. What are the common tools used? Is data scientist even the correct term? Can anyone provide examples of great job descriptions for data scientists?
by uptownfunk on 4/7/17, 5:13 AM
1. Someone with an understanding / ability / passion to understand your business process. This helps you orient the DS in such a way that their analyses will be conditioned to be useful to the business (vs. randomly analyzing the data to satisfy some intellectual curiosity..)
2. Someone who can take what they've learned about the business, and use that to think critically about the data. What is the problem that would help the business to solve? How can we use the data to answer it? What are some hypotheses/potential drivers that influence the problem at hand? What is it worth to the business to analyze / answer the business question?
3. How to convert this analysis/brainstorming into an actual plan. Create a list of analyses and begin executing on them by writing code in either SQL/python/R/etc. They should be able to then tell the story with their analyses as well as visualize what it is they are trying to convey.
4. Translation of results to the business. How to effectively communicate the results of your analysis in such a way that the business can actually make use of your analysis. This is where a lot of DS's suffer because they're so used to nerding out over data it can be hard to actually speak anything a normal person would understand.
I think if you can find someone who ticks the above boxes, you'll be at a good starting point for an effective DS. It also might be good to break down these roles into a team of DS's depending on what size team you're going for. Happy to chat about this stuff anytime. Thanks.