Data Scientist (Brooklyn Nets - Basketball Operations)

Brooklyn Sports & Entertainment•New York, NY

1d•$150,000 - $170,000•Onsite

About The Position

The Brooklyn Nets Basketball Operations department is seeking a passionate, creative, and highly analytical Data Scientist to help advance the organization's basketball analytics capabilities. This role is dedicated exclusively to supporting the Brooklyn Nets Basketball Operations team and will develop, deploy, and continuously improve predictive models, analytical frameworks, and data visualization tools that directly influence basketball decision-making across the organization. Working closely with front office executives, coaches, scouts, and fellow Basketball Analytics team members, this individual will transform complex basketball data into actionable insights that inform player evaluation, roster construction, game strategy, player development, and organizational planning. This role requires both strong machine learning expertise and a deep passion for basketball, along with the curiosity to challenge existing methodologies and introduce innovative approaches that push the organization forward. This position is part of Brooklyn Sports & Entertainment but is dedicated exclusively to the Brooklyn Nets Basketball Operations department. Unlike many roles within the organization that support multiple business units, this role works directly with the Brooklyn Nets and their Basketball Operations leadership to drive basketball strategy and decision-making.

Requirements

3–5 years of professional experience in data science, machine learning, predictive modeling, or a related analytical field.
Bachelor's degree or higher in Data Science, Statistics, Applied Mathematics, Computer Science, or a related quantitative discipline, or equivalent practical experience.
Demonstrated experience developing, testing, and deploying complex machine learning models.
Strong programming skills in Python, R, and SQL.
Experience with modern data science libraries including Pandas, NumPy, Scikit-learn, XGBoost, PyTorch, TensorFlow, or similar frameworks.
Experience working with large, complex datasets and production machine learning environments.
Experience using GitHub, version control, and collaborative software development practices.
Strong analytical thinking with exceptional attention to detail.
Ability to communicate complex analytical concepts to both technical and non-technical audiences.
Excellent written, verbal, and presentation skills.
Strong curiosity, creativity, and passion for identifying new basketball metrics and analytical approaches.
Demonstrated ability to thrive in a fast-paced, collaborative, and continuously evolving environment.
Genuine passion for the NBA and the game of basketball.

Nice To Haves

Experience with Snowflake.
Experience developing interactive analytics applications using R Shiny, Tableau, Power BI, Plotly, or similar visualization platforms.
Experience with JavaScript visualization libraries including D3.js, Victory, Recharts, or Nivo.
Experience applying computer vision techniques to sports analytics.
Experience working with player tracking technologies such as Hawk-Eye or similar spatial tracking systems.
Experience analyzing sports science, player performance, or medical datasets, including injury forecasting.
Strong understanding of modern basketball analytics methodologies and advanced metrics.
Experience working with cloud-based analytics platforms such as AWS, Azure, or Google Cloud Platform.

Responsibilities

Enhance and improve existing player evaluation models while developing new predictive metrics that support basketball decision-making across the Basketball Operations department.
Design, develop, deploy, and maintain machine learning models that generate actionable insights for roster construction, player evaluation, scouting, player development, and game strategy.
Evaluate model performance and establish monitoring frameworks to ensure predictive accuracy, reliability, and continuous improvement.
Build intuitive and visually compelling dashboards and data visualizations that improve the accessibility and adoption of analytics products throughout Basketball Operations.
Partner with Basketball Operations leadership, coaching staff, scouting, and front office personnel to identify analytical opportunities and translate business questions into scalable analytical solutions.
Collaborate with members of the Basketball Analytics team to design and implement basketball software tools and research initiatives.
Critically evaluate existing metrics and analytical methodologies while identifying opportunities to improve current models or create entirely new approaches.
Analyze large and complex basketball datasets, including player tracking and event-level data, to uncover meaningful trends and competitive advantages.
Document analytical methodologies, model assumptions, and technical processes to support knowledge sharing and long-term maintainability.
Stay current with emerging developments in machine learning, artificial intelligence, basketball analytics, and sports technology to bring innovative ideas to the organization.