Jane Street

Quantitative Researcher

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Job vacancy: From now on
Permanent position
Permanent position
International excluding Germany
Entry from the 21.09.2026
Position number 120715

Description

About the position

We are looking for Quantitative Researchers to help us build models, strategies, and systems that price and trade financial instruments. You’ll work side by side with experienced researchers who are committed to teaching, guiding, and supporting our newest hires, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets.

At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and work together to train models, architect systems, and run trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing tens of thousands of high-end GPUs. Depending on the day, we might be diving deep into market data, tuning hyperparameters, debugging distributed training performance, or studying how our model likes to trade in production.

We don’t believe in “one-size-fits-all” modelling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep learning, depending on what best fits a given problem. The most successful researchers will be driven by a curiosity for how their contributions fit into the larger picture of our trading operations, and how to adapt their findings into actionable strategies.

About you

If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. If you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in. You should be:

- Able to apply logical and mathematical thinking to all kinds of problems
- Intellectually curious; eager to ask questions, admit mistakes, and learn new things 
- A strong programmer who’s comfortable with Python
- An open-minded thinker and precise communicator who enjoys collaborating with colleagues from a wide range of backgrounds and areas of expertise
- Fluent in English

Most candidates will have experience with data science or machine learning, but ultimately, we’re more interested in how you think and learn than what you currently know. PhD or other research experience is a plus.

If you’d like to learn more, you can read about our interview process and meet some of the team.

Your skills

Field of study preferred
  • Engineering sciences
    • Architecture
    Civil engineering
    Biological engineering
    Chemical & process engineering
    Electrical engineering & information technologies
    Geodesy & geoinformatics
    Informatics
    Mechanical engineering
    Material sciences & engineering
    Mechatronics & information technologies
    Optics & photonics
    Other fields of study
    Engineering Structures
    Mobility and Infrastructure
    Regional Science
    Water science engineering
    Mechanical Engineering
    Energy Engineering and Management
    Mobility Systems Engineering and Management
    Remote Sensing and Geoinformatics
    Management of Product Development
    Information System Engineering and Management
    Technology and Management in Construction
    Biomedical Engineering
    Computer Science
    Electrical Engineering and Information Technology
    Mechatronics and Information Technology
    Medical technology
    Photon Science and Technology
  • Natural sciences and Technology
    • Applied geosciences
    Biology
    Chemistry
    Chemical biology
    Geoecology
    Geophysics
    Food chemistry
    Mathematics
    Meteorology
    Physics
    Other fields of study
    Mathematics in Technology
    Meteorology and Climate Physics
    Applied Environmental Informatics and Earth Observation
    Computational and Data Sience
    Geophysics
    Meteorology and Climate Physics
    Physics
    Techno-Mathe­matics
  • Other e.g. teaching degrees
    • Other fields of study
    German
    Philosophy / Ethics
    Sports
    Biology
    Chemistry
    Geography
    Computer Science
    Engineering Education
    Mathe­matics
    Natural sciences and Technology
    Physics
Favored career stage
  • Graduate/Beginner

This is what the workplace looks like.

Sector
  • Finance & accounting
Working time model
Full-time
Language at workplace
English

Company information

Type of company
Corporation

Contact

Mrs. / Ms. Ariana Kamboj
Jane Street
2½, Devonshire Square
EC2M 4UJ London
United Kingdom
Tel: +44 020 3787 3200
E-Mail: Please log in to read the stated e-mail address
Company address

Jane Street
2½, Devonshire Square
EC2M 4UJ London
United Kingdom
Telefon: +44 020 3787 3200
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