AMA: Former no-name IB Analyst --> Data science/Artificial Intelligence position at large quantitative hedge fund

Hi All,

I'm an ex-IB analyst at a no-name boutique in a major city. I recently left my job at the boutique after a year and a half for a new position in data science/artificial intelligence at one of the largest quantitative hedge funds in NYC. My career path sounds a little bit strange to many people, but in a nutshell, I like many students out of college was really enamored by the idea of working in IB and the "exit-opps" associated with IB. I really wanted to work for a large bank, but my interview skills were not the greatest, and I ended up working at a small boutique for a year after college. My plan was to lateral to larger bank after a couple of years.

Made me think twice about IB career...

However, working at the boutique really made me think twice about pursuing a career in IB, I felt that at the entry-level at least, the work was really not intellectually stimulating and even though I got to work on a lot of transactions (I closed 2 transactions while I worked there), I felt that I wasn't really developing as many sought after skills as I hoped. Granted, I now know how to make a powerpoint and an excel model better than I did before I started, but being able to make a powerpoint presentation or an excel model wasn't exactly rocket science in the grand scheme of things.

I also realized that I probably would not succeed in IB, which at the partner level would be completely driven by the ability to build relationships, etc. Given my lack of ability with networking, I felt that it would be very difficult for me to climb to that level. And moving to private equity didn't sound that much better either, as it would be a fairly similar role except you didn't have to write CIMS, which was one of the things I most disliked about IB.

Interest in AI/Machine Learning

While I was working at the boutique, I was reading a lot of articles in my spare time about AI/Machine Learning and the transformative effects that this technology could have on society and it got me interested in exploring this further. I knew how to write some basic code from high school, as I used to like writing simple video games in Java as a hobby (yes, I am kind of a nerd), and some basic calculus and statistics from courses in college, but I knew absolutely nothing about AI/Machine Learning.

I spent hours after work watching youtube videos, reading academic research/blogs, and working with courses on Udacity, and just teaching myself the basics. After several months of pretty intense studying, I started building machine learning models and started competing in machine learning competitions on Kaggle. My first couple of competitions, my models basically were in the bottom 20%. But I kept on making improvements, and experimenting with different features, algorithms, hyper parameters etc. and making small improvements to my models, and my score slowly increased and I consistently ranked in the top 10 - 20% in new competitions.

Sent out 40-50 resumes

At this point, I felt much more confident in my own technical abilities and started to apply to new jobs. I added my projects to my resume, and basically applied online whenever a job came out. I didn't care where I worked, but I wanted to work in data science/AI/machine learning. I sent out about 40-50 resumes, and heard back from two companies for interviews. One was a fintech company that used AI/machine learning for commercial lending, and the other company was a large quant hedge fund/trading firm.

I really enjoy my current position, and I just about doubled my salary from my IB position before, but most importantly I feel that I am learning a ton everyday.

Feel free to AMA about my professional experiences!

Comments (27)

Most Helpful
Feb 14, 2019

Very interesting/unconventional transition! How the hell did you fit learning ML in your schedule with IB hours ?

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Feb 14, 2019

Thank you! Haha, yes it is very different from other paths. The boutique I worked at was basically a 9-7 job M-F. But the compensation was really poor as in 60k a year base salary and 2k bonus, which was fair I guess given that I got alot of free time.

Feb 14, 2019

What advice would you give to someone who is on the IB route, but has a strong casual interest in ML now?

Also is your position quant trader or researcher? Did you ever fool around with quantopian?

"one for the money two for the better green 3 4-methylenedioxymethamphetamine" - M.F. Doom

Feb 14, 2019

I guess to start, what is your background? Do you have a basic understanding of how to code in an object-oriented language? If not I would start there, pick up a book (I went to my city library) on Python. Second, I would review statistics and college-level calculus (partial derivatives, etc.). Lastly, after you get hang of the above, I would start with some ML Udacity or Coursera courses. Sorry for plugging them, but most of their courses are free, and without these two resources I don't think I could have done it in such a short period of time. To answer your second question, I am in a researcher position.

Also keep in mind, transitioning from IB --> data science, was a pretty difficult process for me. I would say it would probably be more difficult than going into PE or like a fundamental analyst position at a hedge fund from IB, because none of the things I learned in IB is applicable to my current job, and I would say 95% of my current co-workers came from engineering/mathematics backgrounds in silicon valley or phd programs.

So I guess my point is, don't feel like you need to work in IB for a year to go into data science.

    • 1
Feb 14, 2019

Background is very quant heavy: Graduate coursework in math and economics

Currently still a junior, but I have very scattered interests. I've written some ok quantopian algorithms that involve ML, and am solid in python but nothing else. I think the reason I'm pushed towards IB is the job security and guaranteed paycheck/exits. I've recently been feeling unsure about that path, as I do really enjoy working with more challenging math problems and the like.

"one for the money two for the better green 3 4-methylenedioxymethamphetamine" - M.F. Doom

Feb 14, 2019

Amazing story, thank you for sharing. Did you go to a target school/graduate with a stellar GPA, or were the side projects/competitions enough to secure an interview at the firms you mentioned?

Feb 14, 2019

Well, I went to a target school for IB haha, but I don't think that factored into their decision to hire me for this position. My GPA was a 3.6, but I don't think anyone has ever asked me about it. I don't think most places care about your GPA as much as in IB, given that a 3.6 in finance is not exactly comparable to a 3.6 in Physics or Engineering as an example. But I would say that if you majored in STEM, that would be very helpful.

The projects/competitions helped me secure these interviews and taught me the necessary technical skills to pass them. I listed my Kaggle account on my resume, and they could see online the models I've built and my rankings in competitions.

    • 1
Feb 14, 2019

Really cool story and super congrats on the transition. Are you a quant (alpha development) on a team or are you on a centralized data science team building models using datasets?

Feb 14, 2019

Hey thanks, I'm on a centralized data science team that does the model building. A big part of my current job is processing and cleaning the data we receive so that it can be used to train the models that my colleagues build. I'm not technically a data scientist, but I work hand in hand with the actual data scientists on the team.

Feb 14, 2019

Don't be so modest :) 80% of a data scientist's job is processing / cleaning. I really admire your ambition and drive in changing course. I hope going forward it proves more intellectually fulfilling than IB.

Did you ever consider moving into PE / fundamental funds that have data science teams like coatue?

Also, how important do you think the Kaggle a/c was for landing the role?

Feb 14, 2019

n/A

Feb 19, 2019

Thanks for your sharing. I am also a guy working in some non-name IB industry, but without the passion for networking, I get the same idea that it is a kind of waste of time for pursuing a career in such field. AI/Machine Learning is quite interesting. From your story, the final working opportunity is still finance related, do you want to change to a more tech oriented company like Google or something else?

Feb 19, 2019

Yes absolutely! I could definitely see myself moving in that direction. One of the things I love about ML is that basically the same skill set can be applied to any industry/sector from finance to healthcare to law, etc.

To be honest, I am not sure if I have a passion for finance, I am more interested in the technology itself and the application of this new technology, and its impacts on a highly traditional industry such as finance.

Also, I absolutely understand your lack of passion for networking. I am probably one of the worst networkers in my graduating class and I put a lot of effort into improving my networking skills to no avail, but for this job I did zero networking and just applied online. I don't believe in the tech community there is a huge need for networking, as much as in banking or business.

    • 1
Feb 19, 2019

How much longer do you think it will take for a dude w/o CS or Math background to achieve what you did prior to landing your new job? Also, could you talk a little bit about your long-term aspirations?

Feb 19, 2019

Its really tough to say, I guess its probably doable in a year and half? Assuming you are very dedicated to learning and doing projects. You could also consider one of those 1 year MS in applied statistics. I think the benefits of an MS is that it teaches you the fundamentals and also provide you with a STEM degree which is often a requirement for data related jobs.

As for my career aspirations, I'm actually not sure haha, I used to like planning things out long term, but now I kind of just go with the flow and see where things take me.

Feb 19, 2019

I always thought it was too late for me to pick up ML at this point but your post is inspiring. Gonna do some more digging on this path and see if it is plausible. Thanks.

Feb 21, 2019

great story

Array

Feb 22, 2019

Congrats on the transition! I'm currently a software engineer, and have recently started working in ML in my role at Bloomberg. Like you, I really enjoy the work and find it highly intellectually stimulating. Out of curiosity, which hedge fund did you join?

By the way, annual comp in ML roles can go far above $200k. I'm earning slightly more than that now with 2 YOE and a STEM non-CS bachelor's degree. At Apple, Google, FB, Two Sigma and other top companies, experienced ML engineers can earn $350k+ in annual comp as a new hire. STEM PhD new grads can land data science and ML offers paying $200k in annual comp, with no experience. Check www.levels.fyi for more free tech company and hedge fund compensation data.

Apr 18, 2019

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Sep 30, 2019

I know this is an old thread but if you're still around:
- what programming language do you use the most? aka: what is the most important language to learn?
I currently work with SAS and SQL (joining datasets and cleaning data) and I'm learning Python and R. What would you suggest I focus on if I want to be a data scientist (HF or S&T).
- does the CFA matter with what you're doing? I ask because I have no background in finance. My undergrad is in Statistics and my work is more in the data reporting realm than actual statistics.
Thanks

Sep 30, 2019
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Sep 30, 2019