{"id":1289767,"url":"https://alion.io/job/millennium-management-quantitative-researcher-data-infrastructure-signal-development","title":"Quantitative Researcher -Data Infrastructure & Signal Development","company":{"id":704283,"name":"Millennium Management","domain":"mlp.com","url":"https://alion.io/company/millennium-management","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":85,"open_postings":65,"ghost_share":0,"stale_share":0.385,"repost_share":0,"time_to_fill_p50_days":88,"computed_at":"2026-10-23T05:54:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":200000,"currency":"USD","period":"year","gross":null,"usd_annual":200000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Polars","optional":false},{"name":"Python","optional":false},{"name":"SciPy","optional":false},{"name":"Time Series","optional":false},{"name":"Claude Code","optional":true},{"name":"KDB+","optional":true}],"status":"live","first_seen_at":"2026-06-08T00:00:00Z","employer_posted_date":"2026-06-08","last_verified_at":"2026-10-23T09:58:45Z","board_verified":true,"closed_at":null,"days_open":137,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":137},"description":"Quantitative Researcher -Data Infrastructure & Signal DevelopmentPlease direct all resume submissions to  and reference REQ-29602 in the subject.\nOverview\nWe are seeking a versatile quantitative researcher with strong data engineering skills to join a newly formed systematic equities pod focused on intraday mean reversion and market microstructure strategies.\nYou will be responsible for building and maintaining the research data infrastructure, and for developing and testing trading signals using statistical and machine learning methods. This role combines data engineering rigor with quantitative research creativity.\nYou will work directly with the Portfolio Manager to turn raw market data into actionable trading signals.\n Principal Responsibilities\nBuild and maintain the research data pipeline: ingestion, cleaning, normalization, and storage of tick-level and minute-bar equity data\nDesign and Implement a high-performance research environment using Python, Polars for interactive analysis of large datasets\nDevelop, backtest, and validate intraday alpha signals using statistical methods and classical machine learning (Lasso, Ridge, tree-based models)\nPerform feature engineering on market microstructure data: order flow, spread dynamics, volume profiles, and cross-sectional patterns\nBuild automated backtesting frameworks with realistic transaction cost modeling and slippage estimation\nCollaborate with the C++ developer to publish validated signals into the production trading engine\nMonitor live signal performance, detect regime changes, and maintain signal quality over time\nDocument research findings, maintain reproducible research notebooks, and contribute to the team knowledge base\nRequired Skills/ Qualifications\nBachelor's or Master's degree in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or a related quantitative field • 3+ years of experience in a quantitative research or data-intensive role in a buy-side or sell-side financial firm • Strong programming skills in Python with deep proficiency in Polars, Pandas, NumPy, and SciPy\nSolid understanding of statistical methods: regression, time-series analysis, hypothesis testing, cross-validation • Familiarity with equity markets, market microstructure, and intraday trading dynamics • Strong data engineering instincts: schema design, data quality, pipeline reliability • Detail-oriented with strong problem-solving skills and intellectual curiosity • Excellent communication skills and ability to work In a small, fast-paced team\nPreferred Skills / Experience\nExperience with tick-level or order-book data analysis\nFamiliarity with Apache Arrow, Parquet, and columnar data formats\nExperience with kdb+/q for time-series data\nFamiliarity with Al-assisted development tools (Cursor, Claude Code)\nMillennium offers a total compensation package which includes a base salary, discretionary performance bonus, and comprehensive benefits. The estimated base salary range for this position is $150,000 to $200,000, which is specific to New York and may change in the future. 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