Sergei on Quantitative Research and Collaboration at Jane Street

A Jane Street researcher describes long-running quantitative projects, working with traders and developers, and the value of continued learning.

SeSergeiSpeaker · Researcher
Channel
Jane Street
Published
Jan 11, 2023
Video
3:10
Read
2 min
Original
English
Open on YouTube
Scroll to read and the video shrinks to the bottom-right corner. Captions follow your reading language.
Reading languageAvailable in 2 languages
You're reading the original English.
SUMMARY

In 30 seconds

Sergei, a researcher in Jane Street’s New York office, describes the variety of quantitative research projects and his daily collaboration with traders. He also discusses useful university subjects, pursuing work that genuinely interests you, and the firm’s investment in training.

  1. 1Research takes timeProjects vary, but many involve difficult quantitative questions and can last months.
  2. 2Working across rolesSergei works with traders every day and also interacts with researchers and developers.
  3. 3Follow your interestsHe encourages candidates to work on projects they care about, with statistics or coding relevant to the work.
  4. 4Learning on the jobHis first-year training included classes on options, bonds, and statistics.

Takeaways

  1. Quantitative research projects can take months and cover a range of problems.
  2. Research can involve daily collaboration with traders as well as work with other researchers and developers.
  3. Probability, statistics, and basic programming have been useful in Sergei’s work.
  4. Sergei advises candidates to pursue projects they care about and says related quantitative or coding experience can help.
  5. Internal training can cover financial products and statistical topics.
FULL TEXT

Read the edited text by chapter

Transcript only
01

Research and collaboration

Sergei describes quantitative projects and an example involving stock and option prices. He discusses working with traders, developers, and fellow researchers.

I work as a researcher at Jane Street, where I started in February 2021. Research projects vary widely, but many involve difficult quantitative problems and take months rather than a day or a week.

One project I particularly enjoyed involved thinking about how stock prices move over time and how those movements might affect option prices. I find that a really interesting problem.

How much you interact with developers or traders depends on your preferences and projects. I interact with traders every day and currently sit alongside them. I also work with other researchers and sometimes with developers.

I work with so many people that I sometimes forget who is formally on my team—it can feel as though everyone is. People are kind and friendly, and I am often impressed by the ideas they come up with.

02

Preparation and learning

He shares advice for candidates and identifies useful college courses. He also discusses publication and the firm’s internal education.

My main advice is to work on something you are passionate about. I hope that enthusiasm comes through in an interview. It can also help if your work relates to ours, for example through statistics or coding.

Looking back at college, the courses that feel most relevant to my job are probability, statistics, and basic programming. Researchers generally do not publish much or attend conferences, although I have seen it happen when someone is passionate about it.

One thing I appreciate about Jane Street is its focus on education. During my first year, the firm put me through classes related to my work, including how options and bonds work and various statistics topics. It was encouraging to see that investment in my learning and growth.

More from this channel

1:48:29EN
JSJane Street· Oct 16, 2026How AI Is Changing Programming: John Krazit and Ron MinskyRon Minsky, John Krazit · Jane StreetJane Street’s AI tooling lead and the Signals and Threads host examine agent infrastructure, security, code review and the changing experience of writing software.Coding agentsDeveloper productivityEvals+2
1:36:37EN
JSJane Street· Sep 23, 2026Aaron Bauer on Teaching Software Engineering in the Age of AIRon Minsky, Aaron Bauer · Jane StreetHow learning goals, active practice and editor design shape engineering education when models can generate the code.AI in EducationSoftware engineeringEducation+2
9 slides1:05:45EN
JSJane Street· Sep 11, 2026Cyrus Omar on Live Programming and a Computational Commons for Humans and AICyrus OmarA demonstration of Hazel shows how immediate feedback, structured collaboration and carefully scoped permissions could support people and AI agents working together.Programming LanguagesHuman-AI CollaborationDeveloper workflows & testing+2
1:25:00EN
JSJane Street· Sep 2, 2026Eric Mannes on Turning Messy External Data Into Trading ResearchRon, Eric Mannes · Jane StreetFrom commodity futures and an Excel risk system to point-in-time datasets and AI, Eric Mannes explains the domain knowledge behind data engineering at Jane Street.Data quality & curationDeveloper workflows & testingInvesting+2
7 slides1:16:29EN
JSJane Street· Aug 26, 2026Grant Sanderson and Alok Puranik: Positional Encodings Through Group TheoryGrant Sanderson, Alok Puranik · 3Blue1BrownStarting with assumptions about attention, they derive matrix exponentials and connect rotations, decay and Jordan blocks to RoPE and ALiBi.Transformers & attentionMathematicsML fundamentals+1
27:39EN
JSJane Street· Aug 21, 20263Blue1Brown and Jane Street on Trading, Machine Learning and CultureGrant Sanderson, Nitya, In Young, Craig, Alok · 3Blue1BrownGrant Sanderson talks with Jane Street colleagues about market making, shared compute, research and the paths that brought them to the firm.Machine LearningFintechCompany Culture+2