Senior Data Scientist

Summary

Join Underdog, the fastest-growing sports gaming company, as a Data Scientist/Senior DS to contribute to the development of personalization models and infrastructure. Collaborate with other data scientists to build and iterate on models for personalized recommendations, targeting, and user segmentation. Lead personalization initiatives, build and deploy machine learning models, design and analyze A/B tests, and collaborate with various teams to bring models into production. Develop clean, maintainable code and translate data insights into actionable strategies. This role requires a degree in a relevant field, 2+ years of experience in data science or a related role, and strong proficiency in Python and SQL. The ideal candidate will have experience with recommendation engines and cloud-based tools. Underdog offers a competitive salary, unlimited PTO, parental leave, a home office allowance, and comprehensive benefits.

Requirements

• A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain
• 2+ years of experience in data science, machine learning, or a related technical role
• Hands-on experience with recommendation engines, targeting systems, ranking models, or personalization algorithms
• Strong proficiency in Python for modeling and data manipulation
• Advanced SQL skills and experience querying large, complex datasets
• Solid foundation in statistics, hypothesis testing, and experimental design
• Familiarity with cloud-based tools and platforms (e.g., AWS, GCP, Snowflake, dbt, Airflow)
• Proven ability to partner cross-functionally and influence product decisions with data

Responsibilities

• Collaborate with other data scientists to build and iterate on models for personalized recommendations, targeting, and user segmentation
• Lead personalization initiatives that span modeling, experimentation, and implementation to improve user experience and retention
• Build and deploy machine learning models such as recommendation systems, targeting algorithms, segmentation, and ranking models
• Design and analyze A/B tests and other experiments to evaluate the effectiveness of personalization strategies
• Collaborate closely with Product, Engineering, Marketing, and Data Engineering to bring personalization models into production
• Develop clean, maintainable code and contribute to reusable pipelines, feature stores, and evaluation frameworks
• Translate data insights into compelling stories and actionable strategies for technical and non-technical audiences

Preferred Qualifications

• MS degree preferred
• Experience with uplift modeling, multi-armed bandits, or causal inference
• Prior work in industries such as fantasy sports, sports betting, mobile gaming, or other B2C tech companies
• Exposure to real-time personalization pipelines or recommender systems at scale
• Familiarity with tools like MLflow, SageMaker, or Feature Stores

Benefits

• Unlimited PTO (we're extremely flexible with the exception of the first few weeks before & into the NFL season)
• 16 weeks of fully paid parental leave
• A $500 home office allowance
• A connected virtual first culture with a highly engaged distributed workforce
• 5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents