FANG to Quant Role?
I am a research scientist in ML at one of FANG with 8 years of experience post PhD. This is my second FANG role and I am bored with big tech. Relatively senior now, L7, which means 7-800K annually.
I get approached by some headhunters saying I should interview with hedge funds and prop trading firms for a quant role. Honestly, I would love a role like that, but it needs a lot of interview preparation and not sure if they will match my current compensation. Is it worth it to spend my time trying for these roles and is it worth taking the risk given that I am established in big tech now?
As I am writing this I realize it's hard to answer this, so any anecdotes about ml scientists moving from fang to these roles would be helpful.
I never worked in tech, but can give you my 2c...There is a lot of opportunity to do serious machine learning in finance, but I question if the payoff is worth it given your current comp. Finance is extremely competitive and if you don't have a serious passion for investments I do not suggest it. If you do decide to go down this path I would imagine the max first-year comp you'll get is 1.5x your current pay, but with many more hours and much less earnings stability. Obviously your experience may vary, and it is possible some quant firms may pay even more. I would be curious to see how much Yoram Singer gets paid at WorldQuant--it is likely more than he was making in tech, but I have no idea.
If you're bored my suggestion is to start a company of some sort, and perhaps you could start it on the side before you quit (I imagine your hours are relaxed). Thats the only way to get serious money in this world, and with your background I would imagine the VC folks would be slobbering to get a cut. Best of luck!
I came from tech, but was much more junior than you when I got into finance. Given your current compensation, I do not think there will be much upside for you moving into finance. Chances are you might even suffer a pay cut after the guaranteed bonuses in the first year. Bonuses make up a huge part of compensation in finance and unfortunately it can be quite volatile.
Your headhunter if he/she is any good would be able to advise you on this.
As others have said it is definitely a risk. From a comp perspective the quant/HF roles will be higher IF you can be a top performer, if not you will be at the same level or lower (or end up without a job). It is a riskier path, and as someone pointed out, if you love it or are very interested it is worth it, but it is different than tech.
I’ve seen former tech people in the HF space, the focus is different (make beautiful technology, make products people want to use, work on a piece of an overall product and make that excellent etc, vs make money and find things that work, know when to adjust the code, make sure the right dynamics are being captured, etc). If you are being brought in for quant research roles or have any PnL attached you’ll need an interest in the markets and want to understand how they work.
Additionally, there will only be a handful of places that will be willing to match that comp without a track record in this space. They’ll give you a guarantee but after the first year if you aren’t performing you will most likely see a drop in your compensation.
I made a vey similar move from a much earlier point in my career. I would advise against this switch for your particular case. The reasons I'd advise against this are:
1. Worse risk-adjusted returns. Employee retention is better at tech companies than hedge funds. Even if you make a little more money per annum, I think your expected value is higher in tech.
2. Extra hours not worth the compensation differential. You aren't going to make so much more money in quant finance (or rather, it's incredibly unlikely that you do so) that it's worth the extra hours and higher stress job.
3. Job gets to be very repetitive. A systematic alpha research role basically boils down to "get a dataset and run a 30-step process on it to get it tradeable." This can become a serious slog. For me, the most interesting part of the job is figuring out what makes a stock or dataset "work"; in other words, what phenomenon in the market can you capture or front-run? But other than that, it can be quite tedious as you deal with the same data cleaning, the same factor residualization, the same sensitivity testing, etc.
4. There will be a target on your back. You will likely have a first-year compensation guarantee which would beat your FANG compensation. But between that and your relative seniority, this means that you will likely need to produce P&L quickly, or you'll be let go. This doesn't play well with your lack of experience in quant finance. Contrary to popular belief, you can't just throw sklearn at a dataset and make money. It usually takes a couple of years to really develop the industry-specific knowledge to start to generate real alpha and your own research process. Are you willing to accept the fact that after your first year of work, your comp could cut in half, or you could get fired?
As you think about this switch, here are the questions you may want to ask yourself:
1. Why are you bored with tech, and what could you do to change that without switching industries? For example, are you bored because as an L7, you're too busy managing people and projects to get your hands dirty with a dataset? If so, that's fixable. Are you bored because you've only worked on low-impact projects and never really got to see anything impact users at FANG-scale? That's also fixable.
2. How much does compensation matter here? I don't think making an extra 2-300k per year is going to change much about your situation, particularly when you consider that quant finance isn't all that interesting (see previous points). If you're playing for a level shift in comp, you should found a start-up. Given how hot the venture markets are right now, it's actually gotten pretty easy to raise a seed as a senior technical founder, even if pre-revenue.
3. What exactly are you angling for in finance? Are you going for quant research or quant dev? Do you want to be at a purely systematic firm, or would you be fine working as a data scientist for a discretionary (stock-picking) firm? Do you actually have any interest in the stock markets?
In short: you've done the hard work of climbing the promo ladder. L7 is an amazing accomplishment, and you should be proud of that. Given where you're at and the economics of your current role, I think it would be nuts to leave that to enter a new industry where you take on a ton of additional career risk for relatively limited (if any) upside. Instead, I'd be really curious to hear more about why you're bored right now and why you're thinking about finance (maybe you aren't, and you're solely going off of what headhunters say). But I think there are other paths that can either get you similar comp with less career risk, or that have much higher comp potential (i.e. entrepreneurship) without some of the negatives of finance.
Agree with the other posters, most firms won't pay that much for someone without industry experience, and may treat you like a junior person even if they do. The ML in finance is pretty simple compared to what groups like FAIR or Deepmind do, and the work is more about understanding market behavior using various datasets than doing sophisticated ML. You can always trade on your own or start a side business while keeping that job.
Moving from Wall Street to Tech is the way to go right now, not the other way around.
Sunt blanditiis fuga hic debitis illo odit libero quos. Pariatur suscipit aperiam ut est. Aut facilis omnis molestiae quo. Voluptatem laboriosam sapiente delectus modi.
Non provident autem rem est est similique. Cupiditate quasi voluptates optio ipsum dignissimos.
See All Comments - 100% Free
WSO depends on everyone being able to pitch in when they know something. Unlock with your email and get bonus: 6 financial modeling lessons free ($199 value)
or Unlock with your social account...