Design and implement end-to-end pricing, market-making, and risk models for prediction markets. Build data pipelines, research cross-market dependencies and combinatorial products, partner with traders, and develop backtesting, simulation, monitoring, and validation tooling to support live trading and model calibration.
We’re building a new quantitative research team focused on pricing, market-making, and risk models for prediction markets. This is a highly hands-on role for someone who can operate end-to-end: data engineering, research, modeling, and close collaboration with traders, across sports and non-sports event markets and a range of contract types, including single-outcome markets, player props, and parlays.
Responsibilities:
- Build data foundation, transform raw data into pricing inputs
- Research and develop quantitative pricing, market-making, and risk models across sports, non-sports, player props, parlays, and correlated markets
- Model cross-market dependencies, correlations, and portfolio effects, especially for combinatorial products such as parlays
- Partner closely with traders to improve pricing logic, market coverage, and trading performance
- Build frameworks for backtesting, simulation, and model validation
- Create tools to monitor model performance, calibration, P&L attribution, and live trading outcomes
- Help define the tooling, workflow, and research standards for a new team
Requirements:
- Strong quantitative background in statistics, math, ML, economics, or a related field
- Experience building models in trading, sports, betting, prediction markets, or similar domains
- Strong Python/data skills and comfort owning data pipelines as well as modeling
- Ability to move quickly from raw data to research insight to production-ready mode
- High ownership, strong communication skills and comfortable with fast-paced high growth environment
Similar Jobs
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
The IT Infrastructure Managed Services Director leads cloud and network architecture solutions, drives business growth, and mentors teams, ensuring exceptional service delivery and client satisfaction.
Top Skills:
Cloud ArchitectureInfrastructure SolutionsNetwork Architecture
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Design and improve user experiences for human-AI systems by conducting research, usability testing, creating personas and prototypes, collaborating with cross-functional teams, analyzing trends, and building client relationships to deliver human-centered design solutions.
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Senior Data Engineer on PwC's Managed Data, Analytics & Insights team to design, build and manage advanced data ecosystems. Responsibilities include designing data solutions and scalable pipelines, solving complex problems, mentoring junior staff, maintaining high delivery standards, and building client relationships while aligning solutions to business context.
Top Skills:
DatabricksKafka
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
