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Senior Quantitative Researcher - Risk Modeling

1 day ago
United States
Full-time
Senior
Data Scientist
Data Science and Analytics
AWS C++ Machine Learning MLOps Python Rust SQL
Apply Now
Swish Analytics

Swish Analytics

Swish Analytics offers algorithm-driven sports predictions tools for NFL, MLB, NBA, and NHL games on various platforms, helping users make smarter bets and optimize lineups for better results.

Internet Software & Services
1-10
Founded 2014
$2M raised
View All Jobs 5

Description

  • Own end-to-end research and production pipelines for one or more trading strategies.
  • Lead alpha research initiatives using advanced statistical and machine learning techniques.
  • Process and analyze high-frequency tick data, order book snapshots, and market microstructure signals under 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 and traders.
  • Write modular, clean, and efficient Python code and build custom analytics libraries and research frameworks.
  • Lead design reviews and establish data quality and research reproducibility standards.
  • Mentor 1–2 junior researchers and collaborate with trading and infrastructure teams to resolve research and data dependencies.
  • Design and maintain real-time risk monitoring systems, including dynamic position sizing, portfolio optimization, and stress testing frameworks.
  • Collaborate with Trading and Risk Management to define VaR limits, leverage constraints, and automated risk controls.

Requirements

  • 5–8 years of experience in quantitative research, systematic trading, or statistical modeling.
  • Master's degree in a quantitative discipline such as Mathematics, Statistics, Physics, Computer Science, or Financial Engineering strongly preferred; PhD is a plus.
  • Expert-level Python skills with the ability to build production-grade research and trading systems.
  • Strong SQL skills, including 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 and the 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.
  • Proficiency in Rust, C++, or other systems languages for performance-critical components.
  • Experience with MLOps, model monitoring, and adaptive retraining pipelines for regime detection.
  • Background in derivatives pricing, options market making, or volatility arbitrage.
  • Familiarity with FIX protocol, Betfair or Matchbook APIs, and ultra-low-latency trading infrastructure.

Benefits

  • Base salary starting at $155,000.
  • Equal Opportunity Employer status with consideration for qualified candidates regardless of protected characteristics.
  • Background and reference checks may be required at the employer’s discretion.

Interested in this position?

Apply directly on the company website

Apply Now

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