Top-tier systematic trading firm hiring an ML researcher to push the firm's alpha research beyond classical statistical methods.
Compensation
- Base: $250K–$350K
- Total Comp: $500K–$1M
- Structure: Base + Sign-on Bonus + P&L attachment + performance bonus
Role Description
- Design, train, and deploy ML models (deep learning, NLP, reinforcement learning, or large-scale ensemble methods) for alpha generation across equities, futures, and other liquid markets
- Own the full pipeline from research and backtesting to live production deployment
- Mine large, noisy, non-stationary financial datasets to engineer features and signals that hold up out-of-sample
- Collaborate with quant researchers, engineers, and traders to integrate ML-driven signals into existing systematic strategies
Ideal Candidate
- 2 to 5 years of experience applying machine learning in a quantitative research, trading, or comparable high-stakes production environment
- Strong foundations in statistics, applied ML, and time-series/panel data methods; healthy skepticism about overfitting in noisy financial data
- Proficiency in Python and/or C++; experience with large-scale data pipelines and model deployment infrastructure
- PhD or 2 years of industry experience in ML, statistics, CS, or a related quantitative field a strong plus
Will wait up to 12 months non-compete.
