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.

Base salary range: $75,000 - $150,000 USD, plus benefits including Medical, Dental, PTO, and 401k.