In order to be considered for this role, after clicking "Apply Now" above and being redirected, you must fully complete the application process on the follow-up screen.The Basketball Analytics team partners across Basketball Operations to transform data, research, and technology into actionable insights for front office, coaching, scouting, player development, and basketball strategy stakeholders.
As a Basketball Data Scientist, your practical day-to-day and forward-thinking work will focus on turning complex basketball questions into rigorous analysis, clear models, useful tools, and decision-ready recommendations. Working closely with Basketball Analytics, Engineering, and Basketball Operations, you will own high-impact research and projects that connect technical rigor with real basketball insights.
What You Will Do - Own high-impact basketball data science and analysis initiatives.
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- Translate ambiguous basketball questions into clear analytical plans, research designs, models, tools, and recommendations
- Conduct basketball research using statistical modeling, machine learning, exploratory analysis, and domain expertise to uncover actionable insights
- Build, validate, and maintain models that help evaluate players, teams, lineups, tactics, and basketball decision-making questions
- Work with large and complex basketball datasets, including tracking/spatiotemporal data, play-by-play, event data, lineup/personnel data, scouting information, and other internal sources
- Develop tools, workflows, and data products that turn research into decisions.
- Write clean, reproducible code in Python or R for analysis, modeling, reporting, and internal workflows
- Build internal tools, dashboards, visualizations, and workflows when needed to move projects forward quickly
- Partner with the Engineering team to productionalize high-value model outputs, tools, and data products
- Document methods, assumptions, limitations, and outputs clearly so work can be reused, reviewed, and extended by the broader analytics team
- Support basketball stakeholders with clear analysis and communication
- Collaborate with front office, coaching, scouting, player development, and basketball strategy groups to ensure analysis is connected to real basketball decisions
- Communicate complex technical findings through clear recommendations, written reports, visualizations, and presentations
- Help scope problems, prioritize work, and determine when analysis is rigorous enough to inform decisions
- Use basketball judgment to interpret model outputs, identify limitations, and translate findings into practical next steps
- Drive innovation and special projects within Basketball Analytics
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- Stay current with relevant research, modeling approaches, and basketball analytics methods
- Identify opportunities to bring new ideas, methods, and data sources into the organization
- Use unique basketball data and internal context to create models and insights that are difficult to replicate externally
- Other duties as assigned
Growth Areas - Basketball decision-support models
- Develop and refine models that help the organization evaluate players, teams, lineups, tactics, and strategic basketball questions
- Create tools that make model outputs easier to interpret, compare, and apply in basketball contexts
- Improve the way uncertainty, sample size, role, context, and fit are incorporated into analysis
- Applied research and model validation
- Strengthen research standards for testing, validation, backtesting, documentation, and reproducibility
- Explore new modeling approaches and determine when they can improve existing workflows
- Translate research into practical outputs that can be used by basketball stakeholders
- Internal tools and operational workflows
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- Build and improve tools, reports, and dashboards that help stakeholders answer recurring basketball questions
- Partner with Engineering to move high-value prototypes into more durable, scalable products
- Create reusable workflows that improve the speed, consistency, and quality of analytics work
People and Services - Integrated working with Basketball Analytics leadership and team members
- Partnership with Engineering on data products, internal tools, and model deployment workflows
- Support for front office, coaching, scouting, player development, and basketball strategy stakeholders through timely, decision-oriented analysis.
- Cross-functional collaboration to ensure technical work is grounded in basketball context and connected to organizational priorities
What You'll Bring - Basketball Curiosity and Judgment - A strong desire to understand the game, ask better questions, and connect analysis to basketball decision-making
- Technical Rigor - Strong statistical, machine learning, and research fundamentals with the ability to validate work and communicate uncertainty.
- Practical Builder - Ability to move from idea to prototype quickly, while writing clean and reproducible Python or R code
- Clear Communicator - Ability to translate complex technical work into clear, concise recommendations for technical and non-technical stakeholders.
- Ownership Mindset - Comfortable taking responsibility for ambiguous problems and driving work from question to insight
- Collaborative Teammate - Ability to work effectively across Analytics, Engineering, and basketball departments with a service-oriented approach.
- Data Science Foundation - Professional experience in data science, applied science, research science, or a similar analytical field; expertise in Python or R for data science and proficient SQL skills
- Basketball Analytics Experience - Prior sports analytics experience with a college, professional, or NBA team is a plus
