Alok on Quantitative Research at Jane Street

SUMMARY

In 30 seconds

Alok, a researcher at Jane Street’s New York office, explains that researchers work on data analysis, tools and theoretical problems. He discusses learning finance on the job, following individual research interests and preparing for interviews with probability, game theory and problem-solving.

1No PhD requirementAlok says he does not have a PhD and that researchers can learn on the job.
2From data to strategyResearch can involve building datasets, finding patterns, training models and considering trade execution.
3Follow your interestsHe encourages prospective researchers to study problems they enjoy and learn finance on the job.
4Preparing for interviewsProbability and basic game theory are useful; the focus is generally on problem-solving.

Takeaways

A PhD is not required for the research role Alok describes.
Research projects include data analysis, strategy development, shared tools and theoretical problems.
Many researchers learn finance and proprietary trading on the job.
Probability and discrete mathematics are broadly useful, while other subjects depend on the role.
Research interviews emphasize problem-solving rather than prior finance knowledge.

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Research backgrounds

Alok discusses his path to Jane Street and says a PhD is not required. He emphasizes learning on the job.

I’m Alok, and I joined Jane Street’s research desk in New York in 2020. You do not need a PhD to work in research here: I do not have one, and I believe most researchers at the firm do not either. People interested in academia and quantitative research often enjoy similar kinds of problems, but you can learn on the job.

What researchers work on

Projects range from data analysis and strategy development to shared tools and theoretical questions.

A major category of research work is data analysis. That can include the entire process of developing a strategy: building a data set, finding patterns, training models and thinking through the details of a potentially profitable trade.

Researchers also build tools. Someone may notice the same general problem being solved in several places and create a shared version for the firm. Another kind of project involves theoretical questions: taking complicated problems and finding sensible solutions.

Preparation and interviews

Alok encourages people to pursue their own interests. He describes useful mathematical foundations and the emphasis on problem-solving in interviews.

Before joining, work on the research and problems that interest you. Many researchers arrive with little domain knowledge of proprietary trading or finance and learn much of it on the job. Research beforehand is valuable for your own education and curiosity.

People come with varied interests. My own research included information theory and machine learning for clinical applications. Useful background for almost every researcher includes probability and discrete mathematics; beyond that, the most useful subjects depend on your specialty and role.

I found optimization and machine learning particularly valuable. For others, deep learning, theoretical statistics or other topics might be more relevant. When preparing for a research interview, brushing up on probability and basic game theory is useful.

In interviews we generally look for problem-solving skills, not existing domain knowledge of finance or proprietary trading, and we generally do not test for that background.