Nitya on Training and Working as a Quantitative Trader at Jane Street

要約

30 秒でわかる

Nitya, a quantitative trader at Jane Street since 2019, discusses foundational probability, learning to solve difficult problems, and the training new traders receive. She describes a workweek spanning research, trading, monitoring and collaboration across the firm.

1Start with probabilityNitya recommends a serious introductory probability course and a deep understanding of its basic concepts.
2Training on and off the deskNew traders begin with an OCaml and Python boot camp, learn on the desk and practice mock trading.
3Research and tradingShe spends much of her time on short-term research and about 20–30% executing trades or monitoring trading systems.
4Collaboration across teamsHer projects involve developers, traders and researchers across the firm.

ポイント

A deep grasp of introductory probability is important for quantitative trading.
Challenging quantitative coursework can develop general problem-solving skills.
New traders learn programming and trading through boot camp, desk experience and simulations.
Research and collaboration occupy a substantial part of Nitya’s work.

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Preparing for quantitative trading

Nitya recommends foundational probability and challenging quantitative coursework. Programming is useful but can also be learned on the job.

I’m Nitya, a quantitative trader on Jane Street’s New York international ETF desk. I joined the firm in 2019.

For someone who wants to be a quantitative trader here, a serious introductory probability class is particularly valuable. Knowing many fancy theorems matters less than developing a solid, deep understanding of the basic concepts. Programming is also extremely useful, although it is not strictly necessary to arrive knowing it because you can learn on the job.

Beyond that, I encourage students to find a quantitative subject that excites them—physics, computer science, mathematics or something else—and take challenging classes. Working on hard problems prepares you to tackle hard problems more generally. Just as a Division I athlete builds muscle in the gym, you can build your problem-solving skills.

Training and daily work

New traders learn programming and trading through boot camp, desk work and simulations. Nitya divides her time among research, trading systems and outreach.

New traders go through extensive training. They start with a month of OCaml and Python boot camp while learning on the desk. Later training includes mock trading and sessions in which different desks teach new traders about their work.

My day-to-day work varies. I spend most of my time on research, often short-term projects to improve trading or build models using historical data; sometimes a study develops into a trading idea. About 20–30% of my time goes to executing trades or monitoring automated and semi-automated systems, and I also work on outreach.

Responsibility and collaboration

She took on trading and research responsibilities early and later developed her own ideas. Her work involves colleagues across the firm.

I had real responsibilities early. After boot camp and learning about the desk, I was executing trades and doing research within a few months. By six to twelve months, I was developing my own research, project and trading ideas, including ideas that could help the broader desk or other groups.

Working at Jane Street has been more collaborative than I expected. I work with people on my desk, but also collaborate closely on projects with developers, traders and researchers in different parts of the firm.