{"id":594250,"url":"https://alion.io/job/janestreet-dev-quantitative-researcher-2","title":"Quantitative Researcher","company":{"id":7349,"name":"Jane Street","domain":"janestreet.com","url":"https://alion.io/company/jane-street","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":75,"open_postings":169,"ghost_share":0.337,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":141,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":75000,"max_usd":170000,"period":"year","method":"role_country_seniority_unknown","sample_n":159},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Time Series Forecasting","optional":false}],"status":"live","first_seen_at":"2026-08-03T09:30:42Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-17T17:27:55Z","board_verified":true,"closed_at":null,"days_open":75,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":74},"description":"About the Position\nWe 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.\nAt 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.\nWe 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.\nAbout You\nIf 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:\nAble to apply logical and mathematical thinking to all kinds of problems\nIntellectually curious; eager to ask questions, admit mistakes, and learn new things \nA strong programmer who’s comfortable with Python\nAn open-minded thinker and precise communicator who enjoys collaborating with colleagues from a wide range of backgrounds and areas of expertise\nFluent in English\nMost 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. 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