Moving Back into Trading from FAANG

Was a quant researcher. Left my previous fund after 5 years, for a research scientist position in one of the FAANGs working on machine-learning related research. It has been about 3 years now and with all the exciting happenings in the market last year, I am beginning to miss the industry. Looking to move back into trading now.

Any advice or success stories you can share? 

 

OP here. STEM master's degree from a top 10 university. Very much worth it in my opinion. Due to stock performance total comp (base + rsu + bonus) came to around 600-700k last year. Which is at or beyond the top end of the "normal" range for quant researchers in my circle, and at much more reasonable hours (<50hrs week). Also had the opportunity to work with some of the celebs in the field, which was really cool.

 

Can you elaborate more on why you want to move? I'm actually seeing more people move from quant into tech. Actually the main difficulty is passing the technical interviews as many quants don't have strong algorithms and systems design. Also, curious to hear your thoughts on ML infrastructure vs research. I am seeing more and more specialized roles in ML devops and these are now paying more than the applied ML research positions. However, it seems you have done quite well wrt total comp. Are you in a pure ML research team?

 

MLE does pay more than research, but is commoditized and 95% standard SWE work. Most MLE roles in the big firms involve maintaining and tweaking existing systems. I think it's better to be a pure SWE, which pays the same but gives you a wider skill set and more exit options.

 
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Mostly for the excitement, as I mentioned. Just got promoted about a year ago, next promotion is at least another 2-3 years away, if not more. One drawback of working in a large corporation.

I concur with your observation, I see the same trend of quants moving into tech in my circle. Hedge fund space is getting increasingly winner-takes-all, quants face also the issue of rising data costs. This is especially harmful for smaller firms/teams. Tech on the other hand has too much money to spend on hiring, and cannot get enough qualified people. Needless to say, this has driven up compensation in tech relative to those in finance, with the best payoffs coming from startups. Perhaps this explains the moves. 

Well, the definition and standard of quants vary greatly across firms. In my opinion, if one is doing serious quant research, he would definitely have at least undergrad level understanding of data struct & algorithms. Systems design is not required for every role, it's mostly a software eng thing and also not weighted as heavily as data struct & algorithms (in my opinion). Quants like me usually move into research engineers/scientists positions that tests more for grad level math and theoretical knowledge. 

Yes, you are right about the increasing demand for ml ops/ml engineers. Wages for these roles used to be less than research engineers/scientists but have since increased to the same level. In a way they are paid more considering that these roles only require a basic degree whereas the latter usually requires at least a master's. It is all about supply and demand. There has been a lot of work done in ml research, but not enough focus on actually converting these results into proper systems and production. 

My team focuses on applied research. i.e Our deliverables are actual solutions that are deployed to solve some real world problems.   

 

Short of some very rare spots at a few of the larger platforms, I’d say you risk pricing yourself out of the market if you’re expecting a similar level of comp without having your own strats that you can drop in in year 1.

Particularly within ML there are a ton of guys a few years out of academia who have solid experience that will work for half what you made. If I were you I’d stay out, keep your feet up and enjoy getting out of the office in time to catch east coast first pitch.

 

I don't think firms care so much if you switch back and forth, but many of them only want people who are junior (<5-7 years experience) or are PMs bringing in a complete strategy. If you don't fit either bucket, they consider you too old and won't interview you, unless you have some very specialized expertise they want.

 

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