Swish Analytics
Intelligent U.S. Sports Betting Solutions
Senior Quantitative Researcher – Risk Modeling
Location
California
Posted
58 days ago
Salary
$155K / year
Postgraduate Degree5 yrs expEnglishAWSCloudPythonSQL
Job Description
• Own end-to-end research and production pipelines for a strategy
• Lead alpha research initiatives leveraging advanced statistical and machine learning techniques
• Process and analyze high-frequency tick data, order book snapshots, and market microstructure signals with sub-millisecond latency requirements
• Analyze price formation, market liquidity dynamics, and limit order book imbalances across electronic venues
• Build and run Monte Carlo simulations to estimate P&L distributions, risk exposures, and portfolio dynamics
• Develop, backtest, and optimize quantitative trading strategies with rigorous statistical validation
• Interpret complex model outputs and communicate alpha generation mechanisms to portfolio managers
• Write modular, clean, and efficient Python code; build custom analytics libraries and research frameworks
• Lead design reviews and establish data quality and research reproducibility standards
• Guide 1–2 junior researchers through project delivery and model development
• Proactively engage with traders and infrastructure teams to clarify research objectives and resolve data dependencies
• Design and maintain real-time risk monitoring systems across multi-asset portfolios
• Build models for dynamic position sizing, portfolio optimization, and factor exposure management
• Develop stress testing and scenario analysis frameworks for tail-risk events and regime changes
• Collaborate with Trading and Risk Management to define VaR limits, leverage constraints, and implement automated risk controls.
Job Requirements
- 5–8 years of experience in quantitative research, systematic trading, or statistical modeling
- Master's degree in a quantitative discipline (Mathematics, Statistics, Physics, Computer Science, Financial Engineering) strongly preferred; PhD a plus
- Expert-level Python skills; able to build production-grade research and trading systems
- Strong SQL skills; experience with complex queries on tick databases and time-series datasets
- Deep experience with Monte Carlo methods, stochastic calculus, and probabilistic modeling
- Proven ability to develop, backtest, and deploy systematic trading strategies with demonstrable P&L
- Experience processing high-frequency tick data and real-time market feeds
- Familiarity with AWS or similar cloud infrastructure for large-scale backtesting and research
- Track record of mentoring junior quantitative researchers
- Excellent communication skills; ability to present complex quantitative research to portfolio managers and trading desks
- Experience designing enterprise-grade risk management systems with real-time Greeks calculation
- Strong understanding of factor models, correlation structure, concentration risk, and portfolio attribution.
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