Facebook -> Quantitative trading/engineering
Been working at Facebook for a few months now as my first job (graduated Dec 2018), and overall it's been great. I'm thinking of firms like 2Sigma, JSC, Citadel, etc. However, I find my work to not be that technically challenging (maybe because I'm a solutions engineer as opposed to a SWE, although my job is still basically 100% coding), and I'd like to do something a little more math heavy and I'm also interested in Finance. I graduated from an Ivy League school with a BA in Computer Science, but I had quite a weak gpa (I was depressed performed extremely poorly freshman year) Are there any sort of math classes or projects I can work on to seem more qualified for these kinds of roles? Has anyone made this transition before, and what do you think was your most important quality if you did. Or will my weak GPA (especially as someone who graduated so recently) keep me from being a viable candidate at these companies in the immediate future?
Well are you confident in your math skills to pass a quant interview despite the low GPA? Here's a different type of Dynamic Programming problem from quant land, see if you can figure it out without looking it up that you might get in a quant onsite: Say you can roll a 6-sided dice up to 3 times. After the 1st or 2nd roll, if you get a number x, you can decide either to get $x or to choose to continue rolling. But once you decide to continue, you forgo the number just rolled. If you get to the 3rd roll, you'll just get $x if the 3rd number is x and the game stops What is this game worth and what is your strategy?
Thanks for this, it looks fun, currently on the shuttle home but will try it when I get home. In general I am quite comfortable with my math skills, especially probability and statistics
Your die is a random variable X = {1, 2, 3, 4, 5, 6}. Since all values of X have frequency 1/6, the expected value of X is the simple mean (1 + 2 + 3 + 4 + 5 + 6) / 6 = 3.5. You can decide what to do on each turn using a cumulative distribution function, which gives the probability of X taking on a value less than or equal to a value x. The complement, 1 - CDF(x), gives the probability of X taking on a value strictly greater than x. We observe that rolls of the die are independent events. Turn 1: You roll a value x and have two turns remaining. If x = 4, the probability of rolling a value strictly greater than 4 in two rolls of the die is 1 - CDF(4)^2 = 1 - (2/3)^2 = 0.56, or 56%. Therefore you should elect to forego any value equal to or less than 4 on your first turn, because you are likely to roll a value greater than 4 before the game ends. Conversely, if you roll a 5 you should accept the $5 and quit the game, because the probability of obtaining a value strictly greater than 5 is 1 - CDF(5)^2 = 1 - (5/6)^2 = 0.305, or only 30.5%. Turn 2: You roll a value x and have one turn remaining. If x = 3, the probability of rolling a value strictly greater than 3 in one roll of the die is 1 - CDF(3) = 1 - 1/2 = 1/2. In other words you have equal odds of rolling a value greater than 3 on the next turn. Therefore if you roll a 3 or less on the second turn you should elect to forego the value and take a chance at the third turn. Conversely, if you roll a value equal to or greater than 4, you should accept the money and quit the game, because the probability of rolling a value strictly greater than 4 in one roll is 1 - CDF(4) = 1 - (2/3) = 1/3, or a 33.3% chance. The cumulative distribution function will let you easily solve a generalization of this problem to any n number of die rolls. This is a good warm up question, but quant trading firms will generally ask significantly more difficult variations of this.
The core issue here is that you landed solutions engineer at Facebook, compared with a regular swe position at any of the top tech companies. The quant bar at 2sigma, JSC, Citadel is much higher than facebook swe. And your training in undergrad is in CS. If you are interested in those specific funds, then try for the swe path, as that’ll be your only (slim) chance.
Depression due to the academic pressures? If so, I don’t think HFT is a good fit for you. Also you need to be really good at math.
Nah more so due to moving into the middle of woods from a different country (I am from Denmark)
Sorry. I didn’t mean to.... With Facebook on resume, it should not be hard to get interviews, show your strong math skills. Yeah, HFT cares a lot about GPA.
Agreeing with the other answers on here, it’s going to be difficult to transition directly to a quant role at a top firm. Would say either 1) get a quantitative masters degree and then join a tier 2 firm as a quant and work from there, or 2) try to join a quant firm as a SWE and from there work to getting more exposure to the quant side of the firm.
What are the tier 2 firms ? Do you think it is possible to transform from a quant at IB to a quant at hedge fund if someone has Compsci background from top school?
Given your background, it’s not very likely funds will hire you to do quantitative stuff, but rather coding. You either get a quant master from a top school w/ good GPA, or join a fund as a developer then work your way up. Latter has become more difficult in recent years
Interesting, thanks for the response! Another follow up question, which I guess is similar, is do you know how I could offset bad undergrad GPA to do masters? Could I take community college classes in math to prove my math proficiency before applying somehow? I would also be interested in joining as a developer, although at that point it seems like I may as well just stay at a FAANG company