Data Science in Private Equity Outlook

I'm sort of a sell-side quant (I do AI research). I've been thinking about jumping to buyside a quant shop like many of my seniors have but I recently came across the fact that many PE funds like BX are hiring lots of data scientists.

There was a time when I tried to break into MBB consulting for future exit ops to PE. And I regularly think about using DS techniques to find and aid investment decisions. So this is really interesting me.

Do you think this is just a fad? What's the compensation like? Is DS more of a MO role or can it directly be linked to investment decisions?

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Comments (11)

Apr 28, 2021 - 8:34pm

We've used their analysis in our IC memos and the team has helped quite a bit with portfolio company work. It's nascent, but I think it's the future as the industry matures & informational edge becomes more important.

I'd go to a quant shop over DS at a PE firm especially if you're doing AI research. You'll probably get paid more.

Apr 28, 2021 - 8:45pm

dmx3467

My PE firm has a data science arm. It straddles MO/FO. We've used their analysis in our IC memos and the team has helped quite a bit with portfolio company work. It's nascent, but I think it's the future as the industry matures & informational edge becomes more important.

I'd go to a quant shop over DS at a PE firm especially if you're doing AI research. You'll probably get paid more.

What's the TC like for DS at your fund? How about growth and promotion opportunities? Tbh, both fields are pretty interesting to me.

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  • Associate 2 in PE - LBOs
Apr 28, 2021 - 8:50pm

I alluded to this in another post but this is basically the future of industry. You can run dozens of playbooks and eke out insane efficiencies to the tune of 5%+ IRR in modest cases. This is especially true when working with legacy industries like Industrials or Healthcare that aren't familiar with data science optimizations. There are funds being built around data science strategies right now. It is the way to win in the next decade. The problem is that people like Blackstone still treat their data science guys as second class citizens because they don't really get what's going on and how critical it is to have management buy in and availability of key data.

The other thing people don't realize is that there's a compounding effect. A data science team will receive company data (let's say, a Salesforce CRM and Outlook data). They will parse through Outlook metadata to figure out XYZ. Then, say the firm passes on the opportunity and there is a data destruction request. The data science team has to destroy the core data but does not have to destroy the metadata. So all the juicy learnings, they get to keep, and train their algorithm on, which only becomes more powerful in the future.

OP, don't waste your time on garbage opportunities. You have probably the single most important skillset in private equity in the 21st century.

-- Meathead guy who is bad with computers

Apr 28, 2021 - 8:59pm

I alluded to this in another post but this is basically the future of industry. You can run dozens of playbooks and eke out insane efficiencies to the tune of 5%+ IRR in modest cases. This is especially true when working with legacy industries like Industrials or Healthcare that aren't familiar with data science optimizations. There are funds being built around data science strategies right now. It is the way to win in the next decade. The problem is that people like Blackstone still treat their data science guys as second class citizens because they don't really get what's going on and how critical it is to have management buy in and availability of key data.

The other thing people don't realize is that there's a compounding effect. A data science team will receive company data (let's say, a Salesforce CRM and Outlook data). They will parse through Outlook metadata to figure out XYZ. Then, say the firm passes on the opportunity and there is a data destruction request. The data science team has to destroy the core data but does not have to destroy the metadata. So all the juicy learnings, they get to keep, and train their algorithm on, which only becomes more powerful in the future.

OP, don't waste your time on garbage opportunities. You have probably the single most important skillset in private equity in the 21st century.

-- Meathead guy who is bad with computers

What's the pay though?

I understand that DS is important but is it that future PE founders and managers going to come from DS backgrounds important? Or this will significantly reduce cost for us important?

I'll end up applying to both PE DS positions & Quant Research positions at systematic shops since both are interesting. But I'm still curious.

  • Associate 2 in PE - LBOs
Apr 28, 2021 - 9:10pm

There are already funds popping up where the key man founder is not a deal guy, but more on the data side. You are never going to found a firm as a data scientist; you are going to found a firm as a manager who understands the data play and can get a deal guy to work together with.

Don't worry about the pay. Both jobs will fuck you up with cash. My guess is quant moreso at first but you find the right role in PE and you're one of those guys who ushers in a new way of winning in private markets investing which is waaaaaay more unique and lucrative.

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