Swish Analytics logo
Swish Analytics

Intelligent U.S. Sports Betting Solutions

Senior Quantitative Researcher – Risk Modeling

RiskRiskFull TimeRemoteSeniorTeam 11-50Since 2014H1B SponsorCompany SiteLinkedIn

Location

California

Posted

75 days ago

Salary

$165K / year

Seniority

Senior

Postgraduate Degree5 yrs expEnglishAWSPythonSQL

Job Description

Senior Quantitative Researcher – Risk Modeling

Swish Analytics

• 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

  • Minimum of 5 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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