Basketball Data Scientist, Phoenix Suns
On-sitePhoenix, Arizona, United States
Job Summary
Own high-impact basketball data science initiatives by translating ambiguous questions into analytical plans, models, and decision-ready recommendations. Conduct research using statistical modeling, machine learning, and domain expertise to uncover actionable insights from large datasets including tracking, play-by-play, and scouting information. Build, validate, and maintain models for evaluating players, teams, lineups, and tactics while developing internal tools, dashboards, and workflows to turn research into practical outputs. Write clean, reproducible code in Python or R, partner with Engineering to productionalize model outputs, and communicate complex technical findings through clear reports and presentations to front office, coaching, and strategy stakeholders. Drive innovation in decision-support models and applied research to improve uncertainty analysis and workflow efficiency.
Required Qualifications
- Professional experience in data science, applied science, research science, or a similar analytical field
- Expertise in Python or R for data science
- Proficient SQL skills
- Strong statistical, machine learning, and research fundamentals
- Ability to validate work and communicate uncertainty
- Ability to move from idea to prototype quickly
- Ability to write clean and reproducible Python or R code
- Ability to translate complex technical work into clear, concise recommendations for technical and non-technical stakeholders
- Comfortable taking responsibility for ambiguous problems and driving work from question to insight
- Ability to work effectively across Analytics, Engineering, and basketball departments with a service-oriented approach
Desired Qualifications
- Prior sports analytics experience with a college, professional, or NBA team
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