Manager of Basketball Data Science

This is a Full Time Job

Title: Manager of Data Science, Sacramento Kings

Department: Basketball Operations

Reports To: Vice President, Data Science & Planning

FLSA Status: Full-Time, Exempt

Job Summary: The Manager of Basketball Data Science will serve as both a leader and strong practitioner within the Basketball Operations department. In this role, you will empower a team of talented data scientists to create a competitive advantage through analysis, research, modeling, reporting, and data management. Your work will directly inform the franchise's decisions within player evaluation, roster construction, cap management, and long-term planning. This role is ideal for a leader with strong technical capabilities and a passion for using data and insights to drive sustainable success. This position requires unconventional hours including working in the evenings, weekends and on holidays.

Key Responsibilities:
• Lead data science roadmap, aligning initiatives with the front office's competitive goals.
• Provide quantitative and qualitative support for long-term planning, including player evaluation, roster construction, salary cap management, and forecasting.
• Manage and mentor data scientists, establishing best practices for code quality, model validation, and reproducible research.
• Oversee the full data science lifecycle, encompassing everything from model design and development to deployment, maintenance, and updates.
• Partner with scouts, analysts, and executives to identify needs and deliver data-driven solutions.
• Build and maintain reports and analysis that support key stakeholders. Present findings in a clear and compelling way.
• Represents the Kings in a professional manner while maintaining confidentiality.

Qualifications
• Bachelor's degree in a quantitative field such as Statistics, Computer Science, Mathematics, Data Science, Engineering, or Economics. Graduate degree is preferred.
• 4 years of experience leading projects or managing personnel, preferably within a high-performance sports environment.
• Advanced proficiency in R, Python, and SQL.
• Strong experience in applying statistical and machine learning methods to complex datasets, including exploratory data analysis, model validation, and productionizing models.
• Able to communicate insights effectively across technical and non-technical stakeholders.
• Knowledge and experience with basketball analytics and the NBA collective bargaining agreement and salary cap rules.