Teams at Swish Analytics

Monitor live sports markets and support real-time price discovery, risk management, and trading operations. Calibrate prices using market signals and statistical models, identify trading signals and inefficiencies, manage exposure and liabilities, and collaborate with engineers and data teams to improve pricing infrastructure, automation, and model feedback loops.

Develop, test, and deploy production-scale machine learning and statistical models for tennis sports betting. Create contextualized feature sets, run offline and online experiments to improve performance, collaborate with engineering and product teams, follow software engineering best practices, document work, and present results to technical and non-technical stakeholders.

Lead end-to-end research and production pipelines for systematic trading strategies. Conduct alpha research using statistical and ML techniques on high-frequency tick and order-book data, build Monte Carlo simulations and real-time risk monitoring, design position-sizing and stress-testing frameworks, mentor junior researchers, and collaborate with trading and infrastructure teams to deploy production-grade models and risk controls.