Data Scientist - Risk and Trading (Daily Fantasy Sports)
Develops predictive models and analyzes data to manage risk and liability in daily fantasy sports trading operations. Requires DFS/sports betting expertise, SQL/Python proficiency, and comfort with large datasets and off-hours work.
75k – 150k/yr
RemoteData Science
About the role
Responsibilities
Support risk and liability management for DFS operations through data analysis and modeling to identify trends, patterns, and insights.
Develop predictive models and algorithms to understand real-time liability and risk exposure in specific markets and events.
Conduct data wrangling, processing, cleaning, and design processes/tools for monitoring performance and accuracy.
Monitor pricing for real-time odds, player statistics, breaking news; make real-time market adjustments/suspensions; ensure timely/accurate data from external partners.
Build user risk profiles based on behavior patterns and trends; collaborate with product/engineering for DFS personalization.
Automate risk and trading processes to scale for growth; contribute to research and innovation.
Qualifications
Background in computer science, data science, machine learning, mathematics/statistics, or similar.
Comfortable analyzing large datasets.
In-depth knowledge of DFS, sports betting, player props, handicapping, expected value, closing line value; experience with high-volume DFS/sports betting as trader, +EV bettor, or oddsmaker.
Proactive; able to build processes from scratch and challenge industry norms.
Comfortable working off-hours (nights/weekends) aligned with sports calendar.
Knowledge of SQL, Python; familiarity with databases, data warehouses, data visualizations, report building.
Experience with player performance metrics, game outcome predictions, in-game event modeling, real-time sports data feeds and APIs.
Compensation
Base salary range: $75,000 - $150,000 USD, plus benefits including Medical, Dental, PTO, and 401k.
Skills
SQLPythonMachine LearningPredictive ModelingData AnalysisData WranglingSports Data ApisData VisualizationData WarehousesReal-Time Data Processing
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