CRA exit opportunities ?

So I will be interning at one of the big 3 CRAs. My role will be programming and data analysis kind of stuff and not purely engineering.

At worst it will be a glorified spreadsheet gig and at best working with STEM Ph.D.s on the existing code.

What kind of companies/roles (finance and non finance) should I be applying to after my internship with these guys are over?

Also what kind of skills should I be looking to get as the best bang for my buck during the internship?

Bump

If you do not know finance and accounting, learn that. You will then be very valuable if you understand finance and have the programming skills it seems you already possess. Also make sure you are good at Excel, because even if you do it programmatically the output may still need to be in a well designed Excel workbook.

More than happy to tutor you on these things while you wash my dishes. Just let me know

If you dont have PH.D in hard science, i wouldnt go quant / data science route. Your upside is very limited

Lol,no I don’t have a PhD. I’m not planing to go the Data Science route because of the same reasons you have just mentioned.

This is the only internship I got that seemed “Ok”,but hopefully I wanna something more promising after the internship.

So my personal vote was for the non-finance related one. If I had a choice between working a pure tech firm or a finance firm I’d take tech 10 out of 10 because one industry is in decline and the other isn’t. I’d be really cautious if you’re getting sucked into the finance whirlpool that that is what you really want to do.

On a side note, the data science point was interesting, can either of you or CSK elaborate on the point about upside being capped as a non PhD in data science?

You can probably make 3 handle with Phd working on regression models implementations and neural network, but this still be implementation and not developing your own once. Also, most top positions will flat outright require Ph.D

If you want to be in 500+ range you def need Ph.D in that field

The other company was not an option since the recruiter kept changing the terms and conditions so often I wouldn’t be surprised they would terminate the condition before work began (very common in tech companies to have really shitty HR,but this itself was something).

Also the finance company is hybrid role so I can flip it as finance related to finance companies,business related to product management roles and quantsy developer to Software Engineering roles.

As for the whirlpool,I am looking to ideally work in fintech companies or some hybrid role (product manager type) in tech companies. My background is way too weird for a pure finance role I guess.

I would never say never, who knows. I just thought the data science point was interesting because there’s as huge shortage there and I’ve been hearing backlash against using PhD’s there. Also it’s been my part time pet project.

What CSK said,plus “data science” is becoming such an umbrella term these days.

Everything from pulling shit out from SQL and writing Queries to developing Speech recognition algo is falling under this category and most companies just prefer to use the term without there being much overlap between these roles.

So the term “Data Science” is somewhat meaningless for people who are actually working in the industry as it can entail many different things.

Well, it does have a ton of applications, hence the demand. It’s basically people saying we want programmers with more math/stats background. The issue I think is that most people don’t’ want/need PhD’s and PhD’s mostly want to go do bookish things. So I’ve seen a major rolling out of masters programs and heard repeatedly from people in the data science field that the PhD is worthless unless you’re trying to teach somewhere.

It is worthless, just like any degree is worthless, but i promise you (and i know that for a fact) that Top hedge funds / Top tech firms will only hire Ph.Ds for those spots

Hmmm, that seems to be the opposite of what everyone has told me about top tech firms. I’ve heard it for hedge funds, but not the tech roles.

You have to differentiate between people who build actual models and people who implement models.

Makes sense

and people who date models! dont forget!

people who date models > people who build models > people who implement models amiright6?

My wife is a phd data scientist and I would agree with the notion you are capped unless you have it. I’ve met quite a few of her colleagues (in more junior positions) who are abs brilliant but happened to select a near impossible thesis and dropped out just earning a masters. Some of them, despite being more intelligent and having a higher aptitude, fail to climb rank just bc a difference in a paper degree.

That’s pretty helpful, thanks. I’m not looking at making any major moves near term or trying to jump into pure data science roles yet but am sort of circling the field / skill set while I’ve been doing some coursework just to tack on some quantitative skills.