Anitej Khare is currently a 4th year UG student of ME1 who interned at WorldQuant (WQ) as Quant. Researcher (QR) during the summer after his third year.
Motivation:
I was sure that I did not want to go into the mechanical core, and I got that realisation soon enough in my second year. I was very rigid about not sitting in any core mechanical company! I wanted to do something in tech. I wasn’t even considering doing QR. It was a matter of chance that I ended up getting an intern at a QR firm. After the internship, I realised that I wanted to do this because I had a great experience at WQ and enjoyed the projects I got to work on.
Preparation:
Probability and statistics are very crucial, along with Data Structures and Algorithms. I did MTL108 and COL106 to cover these topics, and I did well in both. MTL108 gives you an essential background and basic ideas which you must know if you’re going to sit for QR. COL106 helps develop algorithmic thinking, and more than anything, it makes you write a lot of code because of the large size of assignments, so it’s an excellent introduction to writing programs.
After phase 1, I did a lot of CP for about six months and the general quant prep. COL351: Analysis and Design of Algorithms course also helped a lot in the interview. For tech, giving Codeforces contests and solving leetcode problems is highly recommended as a standard set of questions gets repeated. For Quant. Brainstellar and going through some classic books like Xinfeng Zhou - A practical guide to quantitative finance interviews (the book is more suited for placements, though, and Brainstellar is maybe enough for internships) is also good.
Application and Selection procedure:
During the first phase of the internship process, I wasn’t very confident about tech skills, but that was the only domain I applied to. I did a fair bit of prep, but it was not enough to compensate for the branch disadvantage. Most tech firms don’t open for ME1, and the few that did open, I wasn’t well prepared for them.
My journey in getting the intern at world quant was non-standard, and it was not very direct. World quant didn’t come in the first week or two of the internship drive, they came somewhere in mid-March which was very late, and in fact, I was planning to do a research intern by then. They asked things I was interested in, and I had done the standard Quant prep that people do and brushed up the basics of probability and statistics. I’m also doing a minor degree in CS, so that did help me a lot. WQ had two rounds for the process, and there was an initial CG cutoff. After the test, 8/9 people were shortlisted for the interview, and finally, four of us got selected. I was the only QR intern, and the other three people were for tech profiles. In the interview, they mostly asked me puzzles and probability problems; three 20-minute rounds were back-to-back. In the last interview, they asked me a very open-ended optimisation problem in the final round, which did not have a definitive answer. They were more focused on analysing my capability to think outside the box and look at my approach to a problem that did not have a simple solution. The interview went well, after which they extended the internship offer to me.
A tech company usually looks for a solid skillset in DSA, operating systems, and DBMS concepts. Quant firms are looking for a good understanding of Probability and Statistics and a decent knowledge of Algorithm Design. I think that since I was doing a minor degree in computer science, I ended up picking up the skills that I needed, but Courses can only do so much, and one has to put in effort on their own to prepare for the internship process. I also had a fair bit of luck that WQ came so late, but mostly I got the internship because I was consistent with my preparation.
Internship experience:
It was a very new experience for me as I did not have any exposure to Quantitative finance, mainly as most of these opportunities are not accessible to people other than from circuital branches.
I was a part of their Mumbai office, but unfortunately, the internship happened online. I had to do two projects, the company assigned one, and I could choose from a list of projects for the other. My assigned project was associated with the data science team. This was a research project where I had to implement an idea and conduct statistical tests to check its feasibility. I wanted variation between the two projects, so I chose my second project to be a script development one. I interacted with an extensive set of people worldwide since the company has offices in New York, Vietnam etc. Through my projects, I got a good glimpse into the work of a quantitative researcher at WQ. I felt that the nature of the work was not super collaborative and was, at times, somewhat siloed. Still, I really enjoyed the work culture. Additionally, I had a lot of flexibility. I could work at my own pace, and my supervisors would check in periodically to guide me and give their inputs. I did not know anything about finance, but that wasn’t an issue as they gave me appropriate guidance wherever needed. My conversations with my advisors were always very informal, and I learned a lot from them. Overall, the internship was an excellent experience for me. It gave me a sense of direction about what I want to pursue as a career since this line of work fits well with my skills and interests.
Advice for candidates:
Use your time wisely. Summer after the second year is the ideal time to start your prep. If you wish to sit for quant roles, try doing MTL106/108 in the second year and seeing blogs like Brainstellar. Also, it’s good to get in touch with Competitive Programming and practice the commonly asked problems. While doing courses like COL106 is helpful, one can learn the material on their own, and in the end, it comes down to how much practice you put in.
Written by: Adhiraj Goel