Data Scientist, Market Making
About this role
Automated pricing systems for sports betting often struggle with maintaining market competitiveness and accurate risk management during live events. To solve this problem, FanDuel needs a data scientist to build and improve the predictive models and algorithmic decision systems powering their trading platforms. Working alongside algorithmic traders, quant engineers, and product teams, the person in this role will translate sports and market data into reliable models that enhance execution quality and risk evaluation.
Candidates who thrive in this environment possess strong quantitative backgrounds and enjoy working within fast-paced production environments. The position involves managing data preparation, building simulation tools, and collaborating across departments to refine automated pricing logic. Because live sporting events dictate the schedule, candidates must be comfortable with a flexible routine that includes occasional evening, weekend, and holiday hours.
What you will do
- Develop, iterate, and deploy predictive models and algorithmic decision systems for automated pricing and market making.
- Partner with algorithmic traders and quant engineers to test, deploy, and refine models and strategy logic in production.
- Manage data preparation from collection through cleaning while building robust models with strong feature and model selection.
- Improve quoting, pricing, and exposure-management logic using sports data, market signals, and performance analysis.
- Build backtesting, simulation, and monitoring tools to evaluate model calibration and risk-adjusted performance.
- Create dashboards, diagnostics, and data visualizations for model health, execution quality, and stakeholder communication.
- Work with engineering and product teams to improve trading tools, controls, and operational reliability.
What you need
- Experience in data science, analytics, quantitative research, or engineering is preferred.
- A bachelor's degree in a highly numerate major such as math, stats, econ, computer science, or engineering, or relevant experience is required.
- Strong proficiency in Python or R and SQL is necessary.
- Candidates must have experience building and deploying models for production products and tools.
- Strong verbal and written communication skills are needed to work across teams, locations, and time zones.
- Familiarity with command line tools, GitHub, and object-oriented design and coding is expected.
Nice to have
- Experience with simulation or back testing
- Interest or experience in sports betting, prediction markets, DFS, or fantasy sports
- Familiarity with pricing dynamics, market behavior, or real-time decision environments
Benefits
- Medical, vision, and dental insurance
- Life and disability insurance
- A 401(k) matching program
- Short-term or long-term incentive compensation, including cash bonuses and stock program participation
- Paid personal time off and 14 paid company holidays
- Paid sick time in accordance with applicable laws
Skills and tech stack
Questions candidates ask
What is the salary range for this position?
The applicable salary range for this position is $98,000 - $152,250 USD. This range is dependent on a variety of factors including relevant experience, location, business needs, and market demand.
What are the working hour expectations for this role?
This role requires flexibility around the sporting calendar, including occasional evenings, weekends, and holidays tied to major live events.
What tools and technologies are used on the team?
The position requires strong proficiency in Python or R and SQL. Additionally, team members work with command line tools, GitHub, and object-oriented design and coding.