Quant Research

Hi WSO, I am a final year PhD student of nanotechnology at University of Cambridge. I did my undergrad in Electrical Engineering from Hong Kong. My PhD is very heavily focused on fabrication of semiconductor nanoelectronics devices in cleanrooms (labs), but also requires some modelling/data analysis and hence I am familiar with programming languages like Python. I am aiming to finish my PhD in the next six months, and I am already simultaneously preparing for quant researcher roles to ideally work at a hedge fund in London later this year. Based on my background, what do you think are my chances of landing a quant researcher job? Is there an alternative path that I should consider taking to improve my chances (for e.g. apply for internships instead of directly applying for full-time jobs to gain some experience first)?

Also, to prepare for this role I am referring to the text book called 'A Practical Guide to Quantitative Finance Interviews' by Xinfeng Zhou, also referred to as 'quant bible'. I have heard websites like 'leetcode' are really helpful for the programming part of the interview, and I will be exploring it next. Do you people have any other suggestions for material or resources that I should look into to prepare for quant researcher interview? Looking forward to your suggestions and thoughts. Thank you very much in advance!    

8 Comments
 

Based on the most helpful WSO content, your background in nanotechnology and electrical engineering, combined with your programming skills in Python, positions you well for quant researcher roles. However, there are a few key points and suggestions to enhance your chances:

1. Chances of Landing a Quant Researcher Job

  • Strengths: Your PhD demonstrates strong analytical and problem-solving skills, which are highly valued in quant roles. Your experience with data analysis and programming aligns well with the technical requirements of these positions.
  • Challenges: Hedge funds often prefer candidates with direct experience in finance or quantitative research. Since your background is more academic and technical, you may face competition from candidates with more finance-specific experience.

2. Alternative Path to Improve Chances

  • Internships: Applying for internships at hedge funds or proprietary trading firms can be a great way to gain relevant experience and transition into a full-time role. Many firms use internships as a pipeline for full-time hiring.
  • Networking: Engage with alumni from your university or professionals in the industry through LinkedIn or events. Networking can help you learn about opportunities and get referrals.
  • Target Tier 2/3 Firms: If top-tier firms like Two Sigma or DE Shaw seem out of reach initially, consider applying to smaller or less competitive firms to build experience.

3. Preparation Resources

  • Books: You’re already using "A Practical Guide to Quantitative Finance Interviews," which is an excellent resource. Another highly recommended book is "Heard on the Street" for brainteasers and interview questions.
  • Programming Practice: Websites like Leetcode are indeed great for honing your coding skills. Focus on problems related to algorithms, data structures, and probability.
  • Mathematics: Brush up on linear algebra, probability, and statistics. These are fundamental for quant roles.
  • Courses: Consider online courses in quantitative finance, machine learning, or algorithmic trading. Platforms like Coursera or edX offer relevant courses.
  • Mock Interviews: Practice with mock interviews to get comfortable with the format and types of questions asked.

4. Additional Suggestions

  • Tailor Your Applications: Highlight transferable skills from your PhD, such as data analysis, programming, and problem-solving, in your resume and cover letter.
  • Understand the Industry: Research the specific requirements and expectations of quant researcher roles at different firms. Some firms may value your technical expertise more than others.
  • Stay Updated: Follow industry trends, such as the increasing use of machine learning in quantitative finance, to align your skills with market demands.

By combining your strong academic background with targeted preparation and strategic applications, you can significantly improve your chances of landing a quant researcher role. Good luck!

Sources: Work-life balance and hedge fund interview prep questions from a soon to be PhD grad & single parent, Deciding on quantitive majors/career path?, Quant Researcher in Quant Funds: Dead-End Career Path?, Q&A: Top Quant Firms First Year Comp 250k to 400k, RE: Prop/Quant Trading - Why is it not as big a target as Investment Banking?

I'm an AI bot trained on the most helpful WSO content across 17+ years.
 
Most Helpful

Your chances are good. A technical PhD from Cambridge is exactly what they want. Make sure you can state a clear motivation for why you want to make the move to finance. 

I won't give too much advice as I am not very experienced myself, but one thing I have heard several times when prepping myself is: don't apply until you are ready. When you apply and are asked to interview, you should be 100% prepared for the tests and interview. Quant firms will 'blacklist' you, and when you apply next year, you won't be invited. So read all the interview guides, etc.. The r/quant subreddit has good resources and a wiki -- use this. Also, some websites like tradermath has firm-specific tests that are very useful -- one of my interviews literally used exactly the same tests as the ones available on this website.

Don't think you need to focus too much on networking, you will most likely be asked to interview given your school and PhD, but reaching out to campus representatives, or going to events hosted by the firms (I would guess these happen fairly regularly at Cambridge) won't hurt. 

Other than this they will prefer that you have published research already that is impactful, demonstrating the ability to produce high-quality research as this is essentially the QR job.

Best of luck!

 

Hey, thank you very much for your detailed response - it is very helpful. I have already submitted a scientific paper which hopefully will be published soon, and will be submitting at least another one in the coming months. Although these papers are about my PhD research and not related to finance, I assume they would still be helpful to show that I have the skills and potential to carry out research, and I believe that's what you meant as well?

Also, thank you for the other useful tips you have mentioned and for bringing r/quant and tradermath to my attention, I will definitely be digging into these. Really appreciate your help :) 

 

You’ve got a strong background, and your programming skills help, but the main gap is direct finance experience. You can definitely apply for full-time roles, but if that’s tough, internships or contract roles could be a good way in. Your prep materials are solid—Zhou’s book and Leetcode are great. I’d also check out Ernie Chan’s Algorithmic Trading, Mark Joshi’s quant guides, and brush up on probability, stochastic calculus, and ML if you’re targeting research-heavy roles. Networking is key too—connect with quants on LinkedIn or hit up finance meetups in London. You’re on the right track, just keep sharpening your technical and financial knowledge.

 

Hi, thanks a lot for listing such useful resources. I'll definitely get my hands on the books that you have mentioned after I have finished Zhou's book. With regards to finance meetups, is there a way to find out when they're happening in London? Should I just search them up on LinkedIn or are they advertised elsewhere? Thanks again :)     

 

Unrelated, but what caused the career change?

It’s not uncommon to see someone with a crazy technical phd doing research at a hf/on the sell side. From what I’ve read online, they all seem to have to same reason i.e. didn’t want to drink the academia cool aid and make dough

 

Haha I wasn't very well aware of possible career paths in finance during early years of my PhD, but then became friends with an IB analyst last year who's working at a top firm. Learned quite a lot about finance industry from them, and they suggested me to explore quant roles after learning about my research skills. Long story short - I did my own research after that (reading a lot of forums and watching a lot of videos) and found this field very challenging, interesting, and mentally stimulating, and thus decided to pursue it :)     

 

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