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About Player 15 Group and Role Overview

At Player 15 Group, we are committed to building more than just a team — we’re creating a legacy founded on passion, innovation, and collaboration. Our culture emphasizes constant growth, diversity of talents, and service-centered work, aimed at revolutionizing sports and live entertainment experiences.

The Basketball Analytics team works closely with Basketball Operations to transform diverse basketball data and research into actionable insights supporting front office, coaching, scouting, player development, and strategic decisions.

Key Responsibilities

Lead major basketball data science projects that inform critical decisions.
Clarify complex basketball inquiries into precise analytical strategies, research plans, models, and recommendations.
Apply statistical modeling, machine learning, and exploratory data analysis on basketball data to uncover insightful conclusions.
Develop, test, and maintain models assessing players, teams, lineups, tactics, and other relevant basketball metrics.
Manage and analyze large datasets, including spatiotemporal tracking, play-by-play events, lineups, scouting reports, and internal records.
Create tools, workflows, and products to translate research findings into actionable decisions.
Write maintainable and reproducible code in Python or R for data processing, modeling, and reporting.
Develop internal dashboards, visualizations, and applications to accelerate project progress.
Collaborate with Engineering to deploy model outputs and analytics tools effectively.
Document research methodologies, assumptions, and limitations transparently for team use and extension.
Provide clear analyses and communicate findings to basketball stakeholders.
Partner with front office, coaching, scouting, player development, and strategy teams to align analytic output with real-world basketball needs.
Convey complex technical results through well-crafted reports, visuals, and presentations.
Help define project scope, set priorities, and judge when analyses are definitive enough to guide decisions.
Interpret model results with basketball insight and recommend practical next steps.
Promote innovation and manage special analytics projects within the team.
Stay updated on cutting-edge research, modeling techniques, and basketball analytic trends.
Seek new ideas, methods, and data sources to enhance organizational capabilities.
Leverage exclusive basketball data and context to generate unique models and insights that competitors cannot replicate.
Undertake other duties as assigned.

Growth Opportunities

Refinement of basketball decision-support models to evaluate players, teams, and strategies.
Development of user-friendly tools for interpreting model results in basketball contexts.
Incorporation of variables such as uncertainty, context, player role, and sample size to improve analyses.
Advancement of research standards including validation, backtesting, and reproducibility.
Exploration and integration of novel modeling methods.
Creation of practical outputs for basketball stakeholders.
Improvement of internal tools and analytics workflows.
Collaboration with Engineering to develop scalable data products and dashboards.
Establishment of consistent, efficient analytic practices.

Collaboration and Partnerships

Close interaction with Basketball Analytics leadership and team members.
Work with Engineering on productizing models, tools, and workflows.
Support for basketball stakeholders providing timely, insights-driven analysis.
Cross-functional teamwork ensuring technical excellence and basketball relevance.

Qualifications and Attributes

A deep passion for basketball coupled with strong judgment to ask meaningful questions and connect analysis to basketball outcomes.
Expertise in statistical modeling, machine learning, and rigorous research methods with clear communication of uncertainties.
Proficiency in producing clean, reproducible code in Python or R and strong SQL skills.
Ability to translate technical findings into clear, actionable recommendations for varied audiences.
A proactive, responsible approach to handling ambiguous problems from inception to insight.
Experience collaborating effectively across analytics, engineering, and basketball operations with a service-minded attitude.
Professional background in data science, applied science, research science, or related analytical fields.
Previous exposure to sports analytics, preferably at college, professional, or NBA level, is advantageous.

Diversity and Employment Notes

The Player 15 Group practices equal employment opportunity and values diversity in race, color, religion, sex, national origin, age, sexual orientation, gender identity, veteran status, and disability.

Note: This description reflects the current scope of duties and responsibilities but is subject to change at the employer's discretion.

Basketball Data Scientist

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