Quant Engineer: Data Products (Mid-career / Senior)
Core
Build and run statistical models for Thematic Factor Risk Models (TFM) to decompose stock returns into thematic and traditional risk factors for institutional investors.
Role type
Senior Quantitative Engineer (Data Products)
Builds
Production-ready factor risk models, signal-generation methodologies, and portfolio-attribution outputs.
Domain
Financial data products, quantitative finance, risk modeling
Deliverable
production ML models
Required skills
Python (production), statistical modeling, cross-sectional regression, covariance estimation, shrinkage, back-testing, point-in-time data handling, pandas, Parquet/Arrow, DuckDB, statsmodels, cvxpy
Preferred skills
PyTorch, NLP-generated exposure analysis, task orchestration (Dagster/Airflow), AWS, CI/CD
Technologies
Python, pandas, Parquet, Arrow, DuckDB, statsmodels, cvxpy, PyTorch, Dagster, Airflow, S3, AWS
Responsibilities
Develop statistical models of stock price movements, construct and back-test factor risk models, design and validate signal-generation methodologies, ensure research reproducibility, collaborate with pipelines team for daily production.
Seniority
Senior, hands-on IC
