Millennium
Quantitative Researcher -Data Infrastructure & Signal Development
$150K–$200K
New York, New York · On-site · Full-time · Posted Jun 8, 2026
- Experience
- 3+ years in a quantitative research or data-intensive role in a buy-side or sell-side financial firm.
- Education
- Bachelor's or Master's degree in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or a related quantitative field.
About the job
Build research data infrastructure and develop, test, and monitor intraday equity trading signals for mean-reversion and market-microstructure strategies.
What you'll do
- Build and maintain pipelines and research environments for tick-level and minute-bar equity data.
- Develop, backtest, and validate intraday signals using statistical methods and classical machine learning; model transaction costs and slippage.
- Collaborate on deploying validated signals and monitor their live performance and quality.
What they ask for
- Bachelor's or Master's degree in a stated quantitative field or a related quantitative field.
- 3+ years of experience in a quantitative research or data-intensive role at a buy-side or sell-side financial firm.
- Strong Python skills with deep proficiency in Polars, Pandas, NumPy, and SciPy.
- Knowledge of statistical methods, equity markets, market microstructure, and intraday trading dynamics.
Nice to have
- Experience with tick-level or order-book data; familiarity with Apache Arrow, Parquet, or columnar data formats.
- Experience with kdb+/q or familiarity with AI-assisted development tools (Cursor, Claude Code).
Pay
$150,000 to $200,000 USD base salary
Tools
Python, Polars, Pandas, NumPy, SciPy, Lasso, Ridge, Apache Arrow, Parquet
AI focus
Develop and test signals using classical machine learning, including Lasso, Ridge, and tree-based models. Familiarity with AI-assisted development tools (Cursor, Claude Code) is preferred.
Model-written summary · the original posting is authoritative