Quantitative Researcher
Core
Design and validate quantitative models and algorithms for proprietary trading strategies using statistical analysis, simulation, and machine learning.
Role type
Senior quantitative researcher (proprietary trading)
Builds
Quantitative trading algorithms, backtesting frameworks, and research tools
Domain
Proprietary trading, financial mathematics, high-frequency trading
Deliverable
production ML models
Required skills
Statistical inference, optimization, time-series analysis, algorithm design, financial mathematics, Python (Pandas, NumPy, PyTorch, XGBoost), low-latency system development, options portfolio construction
Preferred skills
None stated
Technologies
Python, Pandas, NumPy, SciPy, scikit-learn, statsmodels, PyTorch, XGBoost, LightGBM, Numba, Polars, Dask, Matplotlib
Responsibilities
Evaluate and improve quantitative models via statistical analysis and simulation; Design methods to analyze market data for new trading strategies; Build computational tools and backtesting frameworks; Formulate trading hypotheses as mathematical/ML models; Apply statistical inference and financial mathematics to diagnose model behavior; Identify gaps in algorithms and propose new approaches; Define design requirements for new trading algorithms; Drive research projects from definition to post-deployment review; Assess model readiness for production; Prioritize research initiatives; Mentor graduate researchers and interns
Seniority
Mid-level (2+ years experience)
