# Data Scientist - Risk and Trading (Daily Fantasy Sports)

**Company:** [Sleeper](https://hotfix.jobs/companies/sleeper)
**Location:** Remote
**Role:** Data Science
**Salary:** $75k – $150k/yr
**Skills:** SQL, Python, Machine Learning, Predictive Modeling, Data Analysis, Data Wrangling, Sports Data Apis, Data Visualization, Data Warehouses, Real-Time Data Processing
**Posted:** 2026-02-06

> 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.

## Job Description

## 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.

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