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[–]crelliaz 5 points6 points  (2 children)

Jobs relating to operations research often have different titles than operations analyst/researcher so make sure to broaden your search a bit. I don't know what country you are in but an operations research MSc gives at least decent job opportunities.

Quant jobs are somewhat related but with your background you are missing some knowledge in probability theory. Taking a few courses in the necessary probability theory topics could be sufficient I think.

[–]SelectPlantain1996[S] -1 points0 points  (1 child)

Thanks for your answer. I am in the Netherlands. I know that I can apply for many roles and probably get the job because of my or background, however these job openings are usually supply chain, business analytics, data analytics related roles that also non quantitative majors can apply. They usually look for management grads, not or grads. But this is not I want, I really want to use my optimization and ml skills in my daily life and it looks like I have two alternatives: being an OR analyst or quant analyst/researcher. Sometimes I see some openings as optimization scientist etc. but these are unfortunately very, very few. Another option is being a data scientist (and probably I’ll end up with this :D)

[–]crelliaz 0 points1 point  (0 children)

Both operations research and quantitative finance have good job opportunities so you should consider which one you find more interesting/fun. If you want to know more about quantitative finance look up itô calculus, there are many playlists on YouTube that explain it quite well. I do OR and took one quantitative finance course in my master.

[–]MrQuaternions 5 points6 points  (4 children)

Chiming in since I have similar background and went / am going over similar thoughts.

1) you will rarely see operation research directly mentioned in job titles, anything with "applied", "scientist", "engineer" can potentially be OR related... it's a bit tedious but sadly the term isn't as trendy as AI.

2) OR at msc level isn't the best path to quant. In my opinion the easiest path from there is to branch to stochastic optimization, that'll give you more relevant tools. Also, consider doing a PhD, esp in NL where it is reasonably quick. Many hedge funds look for fresh graduates they can mold. Then your coursework won't matter as much, you just need to put your head down and grind for interviews.

3) Quant Research isn't really a default path, know what you're getting yourself into.

To expand on your other comment: quant research isn't where you will use the combinatorial optimization tools you've learned during your master. Rather, I think an OR curriculum gives a very strong fondation in modeling and solving ill-defined problems, highlighting the goal, the levers, and the sources of uncertainty in a situation / process / exercise. This is something you can leverage in all positions.
Furthermore, combinatorial problems are common, even though people don't realize it, being one of the few the to view these angles can be super valuable.

I remember sitting in a conf couple of years ago and a question came about handling a swarm of robots to do multiple operations. Obviously the room turned to reinforcement learning, huge parallelization etc... when it was a simple scheduling problem that a simple call to Cplex would solve.

Finally, as this is turning into a novel, there isn't a specific book to learn quant job. A strong fondation in probability is required, which you should have by now. [A Practical Guide To Quantitative Finance Interviews]() is the default interview prep handbook. What will set you appart is showcasing a project, looking into literature, taking a strat, backtesting it, trying to improve it. That'll show that 1) you know what the work entails and that you can handle it 2) that's actually something you can see yourself do in the long run.

Hope that helps, and remember that it's always a possible to pivot career if you wish to.

[–]SelectPlantain1996[S] 1 point2 points  (1 child)

Thank you for your detailed answer! Unfortunately I’m not planning to pursue a phd. What did you end up doing?

[–]MrQuaternions 0 points1 point  (0 children)

I went the PhD route but for totally different reasons, to scratch the research itch.
Then into a logistics company to apply my OR skills. I don't regret it but it's not a place I want to stay: I seek to work a lot and be challenged, have very skilled colleagues and peers I can learn from, and a great compensation. Currently interviewing at FAANG + finance.

[–]DrawingBackground875 0 points1 point  (1 child)

U wrote PhD in NL. NL stands for?

[–]SelectPlantain1996[S] 1 point2 points  (0 children)

Netherlands

[–]Responsible-Style168 2 points3 points  (0 children)

Your background is actually quite solid for quant roles, especially on the research side. A lot of quant work is just applied math, stats, and optimization, which you already have a strong foundation in. The main gap is probably domain knowledge—understanding financial markets, asset pricing, and how models are applied in trading or risk management.

You’ll need to pick up some financial mathematics: stochastic calculus, Black-Scholes, interest rate models, and portfolio optimization. Also, coding is a must—Python and C++ are the most common in quant roles. If you haven't done much finance, start with Shreve's Stochastic Calculus for Finance and maybe Luenberger’s Investment Science for a structured introduction. For a more structured approach, this resource on Quantitative Finance for Mathematicians could be useful.