Market-Making Data Scientist — Hybrid Trading & Modeling

FanDuel; Jersey City (NJ); Hybrid; USD 98,000 - 152,000; Full time

Benefits offered by this job

FanDuel Total Rewards

Job summary

FanDuel seeks a quantitative professional to build predictive models and algorithmic decision systems powering automated pricing and trading for live events. You will translate sports, market, and operational data into models that improve price quality, execution quality, market competitiveness, and risk management.

The role requires flexibility around the sporting calendar and collaboration with traders, quant engineers, and product teams to deploy models from research to production with robust

Qualifications

• Bachelor's degree in a highly numerate major or relevant experience.
• Strong proficiency in Python or R and SQL.
• Experience building and deploying models for production products.
• Experience with simulation or backtesting is a plus.
• Interest or experience in sports betting, prediction markets, DFS, or fantasy sports.

Responsibilities

• Develop, iterate, and deploy predictive models for automated pricing and market making.
• Partner with traders and quant engineers to test, deploy, and refine models in production.
• Manage data preparation from collection through cleaning; build robust models with feature selection.
• Improve quoting, pricing, and exposure-management logic using data signals.
• Build backtesting, simulation, and monitoring tools to evaluate model calibration and risk-adjusted performance.
• Construct analyses in response to questions from trading, product, and engineering stakeholders.

Skills

Data science exp

Python/R

SQL

Production models

Simulation/backtesting

Sports betting

Pricing dynamics

Cross-team comms

Command line tools

GitHub

Education

Bachelor's degree in numerate field

Tools

Production deployment tools

Job description

FanDuel seeks a quantitative professional to build predictive models and algorithmic decision systems powering automated pricing and trading for live events. You will translate sports, market, and operational data into models that improve price quality, execution quality, market competitiveness, and risk management.

The role requires flexibility around the sporting calendar and collaboration with traders, quant engineers, and product teams to deploy models from research to production with robust