Basketball Data Scientist: Translate Data into Wins

Phoenix Suns; Phoenix (AZ); On-site; USD 120,000 - 180,000; Full time

Job summary

The Phoenix Suns are seeking a versatile Basketball Data Scientist to turn complex questions into actionable insights, models, and data products. You will work with Basketball Analytics, Engineering, and Basketball Operations to deliver decision-ready analysis that informs front office and coaching decisions.

You should have strong Python or R programming, solid statistical and ML fundamentals, and the ability to communicate findings clearly to technical and non-technical stakeholders.

Qualifications

• Professional experience in data science, applied science, or research science.
• Expertise in Python or R for data science and proficient SQL.

Responsibilities

• Own high-impact basketball data science and analysis initiatives.
• Translate ambiguous basketball questions into analytical plans and models.
• Conduct research using statistical modeling, ML, and exploratory analysis.
• Build, validate, and maintain models evaluating players, teams, and lineups.
• Develop tools and data workflows to turn research into decisions.
• Write clean, reproducible Python or R code for analysis and reporting.
• Create dashboards and visualizations to move projects forward.
• Partner with Engineering to productionalize outputs and data products.
• Document methods and limitations clearly for reuse by the analytics team.

Skills

Basketball data science

Python or R for data science

SQL proficiency

Machine learning basics

Clear communication

Job description

The Phoenix Suns are seeking a versatile Basketball Data Scientist to turn complex questions into actionable insights, models, and data products. You will work with Basketball Analytics, Engineering, and Basketball Operations to deliver decision-ready analysis that informs front office and coaching decisions.

You should have strong Python or R programming, solid statistical and ML fundamentals, and the ability to communicate findings clearly to technical and non-technical stakeholders.