6 Things You Need To Be Successful At Data Science
As experts in providing mentorship, wisdom, and expertise in helping build out data science teams over the last 12 years, we have come up with the 6 things you need to be successful at data science. Recently, we helped an extremely successful construction software startup scratch build data science. They were the best we have seen yet at going from zero to full enterprise-level data science. So good, in fact, the software company made a case study of their pilot project, inspired us to write an ebook on the importance of figuring out the extremely difficult process of implementing data science at scale, and motivated us to write this article.
But what did they do that was so different? The answer is more than just hiring a person. More than just starting a project. They did a host of things that worked together to prove their value, implement their process, and put themselves in a position to succeed. Here is what they did. They found:
(1) the right employees with the right skill-set and desire to figure out the problem, (this likely isn’t the PhD data scientist you want to hire–see our ebook)
(3) the right culture of leadership-driven demand for data science insight (we have a book on this too. Click Here)
(4) the right software to be what they needed in the beginning, but also to one that could grow with them, (they choose this one)
(5) the right partner (CAN) to provide mentorship, wisdom, and expertise so that the project had a high chance of success, and
(6) the right first project–one that could be conquered quickly, was highly visible, and would have a high ROI.
What thing can you take back to your business to implement that will help you? There isn’t one and that is the point. They were successful because they implemented them all. All. Successful data science only happens when you implement all 6 of these things in tandem. Only 1? Fail. 3, 4, 5? …Fail. Only 6 works. It’s a tall order. Most can’t do all 6. But it’s critical for success.
To understand why requires more reading.
