a) Systematic VC will find/evaluate co's algorithmically. Decisions based on set of rules.
b) Data driven VC has typical investment committee making decisions informed (not instructed) by data
b) Winning the Co.
c) Evaluating the Co.
d) Helping co. post close
Thus- hard to use for sourcing. Also - quickly becoming commoditized
Key difference is systematic makes the decision algorithmically.
Same will be true in VC.
“[Top 3 venture firm] has quietly hired several data scientists. Basically all they are doing is one off projects for their portfolio companies.”
Your vc firm needs some engineers. Could be 3:1 ratio of engineer:ds for this problem; depends on a lot of inputs. But it isn't 0:1.
What is critical in your evaluation of the VC is digging deeper into 1) what problems they are solving with the data, and 2) what resources they are willing to put behind the problems.