Company Description
Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
As we expand our presence on betting exchanges, we're building infrastructure and strategies akin to those found in traditional financial markets. Our challenges are unique, and we hope you're comfortable in uncharted territory.
Role Overview
As a Senior Quantitative Researcher, you will own end-to-end research and production pipelines for one or more trading strategies. You'll lead research initiatives that generate alpha and improve execution quality, mentor junior researchers, and collaborate closely with our Trading desk to translate quantitative insights into profitable systematic strategies while maintaining rigorous risk management.
Core Responsibilities
- 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
Execution & Market Microstructure
- Design and implement transaction cost analysis (TCA) frameworks to measure and improve execution quality
- Build market impact models and optimal execution strategies to minimize slippage across venue types
- Develop real-time monitoring systems for latency, adverse selection, and execution performance metrics
- Partner with infrastructure teams on ultra-low-latency data feeds and smart order routing algorithms
Requirements:
- 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
- Deep understanding of equity/futures market microstructure, order types, and matching engine logic
- Experience building sophisticated TCA frameworks with market impact decomposition
- Familiarity with FPGA or kernel-bypass networking for latency-critical applications
- 5–8 years of experience in quantitative research, systematic trading, or statistical modeling
Nice to Have
- 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 API experience, and ultra-low-latency trading infrastructure
Base salary: Starting at $155,000
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.
