REPE shops known for being very data-driven?
Title says it all, looking for REPE shops that are very data-driven and location doesn’t matter. ++ if they are newer/trending and offer internships. I’m at a semi-target in the northeast US btw.
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In what sense
In the sense that their investment processes, strategies, and/or theses are guided by data science (rather than industry knowledge and relationships)
It’s up to the operators to be data driven and then a REPE fund comes along and decides to invest alongside them. I can think of two operators that are data driven (I have to go back and look them up) but can’t think of any REPE funds that would fit that category
Gotcha, thank you! I'd love to hear those names if you have them.
CSIG Holdings (their senior living subsidiary) has or had an in house data scientist that determined the best possible places to build senior living facilities.
They’re a small team, so probably not a place you could work. I guess it’s a good counterpoint to the other commenters - small shops can be data driven too
Most if not all investment management firms will have a research and strategy operation, this has become a norm because pension fund consultants will score funds/firms on research and ideation (big increase since 2008 issues). Smaller firms may have a person doing this while using outside consultants, while larger ones may have large departments. How advanced they are using data varies, but everyone is having fun in this sector.
Ones I personally know of include USAA, Nuveen, PGIM, Clarion, MetLife, AEW, Barings, Brookfield, CBRE GI, LaSalle, Heitman, Blackrock, Hines, BentallGreenOak. I once you get to a certain size, I think you can assume they have someone in house to manage the process. Smaller ones may outsource practically everything as needed/ad-hoc (like during fund raising).
Any thoughts on who the more advanced research teams are among the firms you listed?
PGIM was one of the very first to have a very advanced research shop (started hiring PHDs back in the 80s/90s). I know USAA has data scientists in their research unit (research headed by a phd). Nuveen and Clarion have pretty advanced teams, based on the people I know there. Those are ones I know for sure.
CBRE GI, LaSalle, Heitman, Hines appear more classic/standard (but I'm not reading their stuff, so I may just not be aware), but I'd bet they are all adding these capabilities or will overtime.
The rest I would be totally guessing. I know Blackrock and Brookfield have some very advanced analytical/quant units, not sure how much they work on real estate strategies.
This is just the direction the world is going. Again, even if the firm doesn't have in-house capabilities, does not mean they are not hiring outsourced consultants doing the same.
stablewood properties in texas.
Funny you mention that, someone also said Lionstone below (if I'm not mistaken, the guy who started Stablewood came from Lionstone)
yea the team at stablewood is great. highly recommend looking into them, they are doing some really cool stuff
How "data-driven" are you talking? Are you talking to the point of using actual programming languages like python, R and other statistical programming to help with the decision making, like a true data analyst or business analyst? If that's the case, you're going to have a hard time finding those types of roles in an REPE shop, at least front office. I find it hard to implement data-driven tools into CRE transactions process due to asymmetry of information. There are many off-market deals that occur because of certain relationships brokers/landlords/lenders have with someone. When this happens you just check that the underwriting and the overall due diligence makes sense enough to buy/sell/hold.
In asset management, I can see it be useful (i.e. a large portfolio of apartments with thousands of units not hundreds like a REIT).
Yes, I meant very Python-driven ... that makes a lot of sense though, thank you!
Python and R are creeping into the job descriptions more and more, just an observation. My analyst is actually learning Python on the side, but they have an econ background and familiar with the standard/old stats packages like Stata/SAS, now Python/R is the new standard. Thus, I suspect it will be minimum criteria in just a few years.
Lionstone in Houston. They have their own GIS and data science team.
Awesome, I'll check it out -- thank you!!
All big/medium size fund managers have these units now. While I love the research these groups do and I think our business is heading into a much more data-driven direction, these groups are really just for the LPs. Yes, the research they do informs strategies and what opportunities we raise capital around, but at the end of the day, folks (yours truly included) are using the data to push a narrative they like or jam a deal they like into a given strategy. They are not the horse pulling the cart for 95% of shops. You'll be hard-pressed to find an acquisition team today using code or heavy computer science as the basis for an investment decision. That may change in the not so distant future, but for now, the reality is that our business runs on napkin math, shiny PPMs, Thursday afternoon beers, and a healthy dose of bullshit.
This is pretty accurate, the use of data/research is generally high level and will have most of its applications in fund raising, setting fund strategies/allocations, and (at some shops) setting the "target" markets and property types. Once the strategy is set and agreed by LPs, there isn't many ways or need for the acquisitions team to use such, especially on deals with leases in place (more applications in development due to long-term nature of uncertain rents/leasing). Deal making is deal making at the end of the day, and real estate assets don't really fit into a "quant" trading strategy by nature.
Gotcha, thanks guys!
this guy real estates
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