Staff Data Scientist

Summary

Join Underdog, the fastest-growing sports gaming company, as a Staff Data Scientist to lead the development of personalization systems and machine learning models. You will act as a technical leader, spearheading end-to-end personalization initiatives. Responsibilities include designing and building complex machine learning models, partnering with various teams, driving experimentation, defining the architecture for scalable systems, leading cross-functional standups, and mentoring junior data scientists. This high-visibility role requires an advanced degree, 6+ years of experience in data science with a focus on personalization, and expertise in statistical modeling and programming. The ideal candidate will also possess strong communication and business acumen. The position offers a competitive salary, equity, unlimited PTO, parental leave, a home office allowance, and comprehensive benefits.

Requirements

• Advanced degree in mathematics, statistics, engineering, computer science, or similar field
• 6+ years of industry experience in data science or machine learning, with a focus on personalization, recommendations, targeting, or user modeling
• Proven experience designing and implementing recommendation engines, ranking algorithms, or uplift models
• Deep expertise in statistical modeling, experimentation (A/B testing), and causal inference techniques
• Excellent Python programming skills, with experience building and maintaining production-ready ML code
• Strong command of SQL and comfort working with large-scale, complex datasets
• Experience working in cloud-based environments (e.g., AWS, GCP) and familiarity with modern data/ML tools and frameworks (e.g., Airflow, dbt, MLflow, SageMaker, Vertex AI, etc.)
• Demonstrated ability to collaborate cross-functionally and translate business problems into data-driven solutions
• Strong business acumen and communication skills: You can explain complex technical concepts to non-technical audiences

Responsibilities

• Lead end-to-end personalization initiatives across the product, from identifying high-impact opportunities to model development, deployment, and testing
• Design and build complex machine learning models, such as recommender systems, ranking algorithms, segmentation models, and targeting solutions
• Partner closely with Product, Engineering, Marketing, and Data teams to implement solutions that improve user engagement, retention, and conversion
• Drive experimentation, including A/B test design, measurement, and interpretation, to validate model and product effectiveness
• Help define the architecture and framework for scalable, repeatable personalization systems and ensure proper model monitoring, governance, and documentation
• Set up and lead recurring cross-functional standups to align and drive forward personalization initiatives
• Mentor and guide junior data scientists, providing thought leadership and technical direction within the Data Science team

Preferred Qualifications

• Experience with uplift modeling, multi-armed bandits, or reinforcement learning for personalization
• Prior work in the fantasy sports, sports betting, mobile gaming, or consumer entertainment industries
• Contributions to building ML infrastructure, pipelines, or reusable personalization frameworks
• Familiarity with real-time recommendation systems or event-stream processing (e.g., Kafka, Flink, Kinesis)

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