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Staff Data Scientist

Underdog

$180,000 - $210,000
Nov 7, 2025
Remote, US
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Underdog aims to build the best products in the sports industry by enhancing user experience and retention through personalized recommendations, targeting, and user segmentation.

Requirements

  • 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).
  • Experience with uplift modeling, multi-armed bandits, or causal inference.
  • Exposure to real-time personalization pipelines or recommender systems at scale.

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.

Other

  • A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain. MS degree preferred.
  • 2+ years of experience in data science, machine learning, or a related technical role.
  • Proven ability to partner cross-functionally and influence product decisions with data.
  • Prior work in industries such as fantasy sports, sports betting, mobile gaming, or other B2C tech companies.
  • This position may require sports betting licensure based on certain state regulations.