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Basketball Data Analyst Jobs (NOW HIRING)

Roanoke College

Head Women's Basketball Coach

Salem, VA · On-site

$50K - $60K/yr

Teaches students the art, craft, and science of the sport of basketball. Develops and directs an ... In addition to on the court performance, provides data analysis for persistence and retention ...

Roanoke College

Head Women's Basketball Coach

Salem, VA · On-site

$50K - $60K/yr

Teaches students the art, craft, and science of the sport of basketball. Develops and directs an ... In addition to on the court performance, provides data analysis for persistence and retention ...

Rose Quarter

Senior Basketball Researcher

Tualatin, OR · On-site

... drive data-informed decisions. DAY-TO-DAY: * Design, develop, and validate analysis systems ... Have strong intellectual curiosity and basketball acumen, with the ability to connect analytical ...

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Basketball Data Analyst information

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$34K

$82.6K

$136K

How much do basketball data analyst jobs pay per year?

As of Jul 28, 2026, the average yearly pay for basketball data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Basketball Data Analyst position, and why are they important?

To thrive as a Basketball Data Analyst, you need strong statistical analysis, knowledge of basketball strategies, data management, and often a degree in mathematics, statistics, or a related field. Proficiency with tools like SQL, Python, R, and basketball-specific analytics software such as SportVU or Synergy Sports is crucial. Excellent communication, attention to detail, and teamwork abilities set standout candidates apart. These skills enable analysts to deliver actionable insights that directly influence team decision-making, player development, and game strategy.

What is a Basketball Data Analyst job?

A Basketball Data Analyst collects, processes, and interprets basketball-related data to provide insights for teams, coaches, and executives. They analyze player performance, team statistics, and game trends to aid in decision-making. Using tools like Python, SQL, and data visualization software, they create reports and models to optimize strategies. Their work helps improve player development, scouting, and in-game tactics.

What are the typical daily responsibilities of a Basketball Data Analyst?

As a Basketball Data Analyst, your daily responsibilities often include collecting and cleaning player and game data, conducting statistical analyses, and creating visual reports or dashboards to present findings. You may work closely with coaching staff to interpret analytics and help inform game strategies or training adjustments based on performance metrics. The role also involves monitoring trends across the league, developing predictive models, and ensuring data integrity. Collaborative teamwork and frequent communication with scouts, coaches, and other analysts are vital parts of the job. This dynamic environment keeps the work challenging and allows you to directly impact a team's success.

More about Basketball Data Analyst jobs
What cities are hiring for Basketball Data Analyst jobs? Cities with the most Basketball Data Analyst job openings:
What are the most commonly searched types of Basketball Data Analyst jobs? The most popular types of Basketball Data Analyst jobs are:
What states have the most Basketball Data Analyst jobs? States with the most job openings for Basketball Data Analyst jobs include:
What job categories do people searching Basketball Data Analyst jobs look for? The top searched job categories for Basketball Data Analyst jobs are:
Basketball Data Analyst jobs near you
Infographic showing various Basketball Data Analyst job openings in the United States as of July 2026, with employment types broken down into 66% Full Time, 4% Part Time, and 30% Contract. Highlights an 61% Physical, 5% Hybrid, and 34% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Basketball Data Scientist, Phoenix Suns

Player 15 Group

Phoenix, AZ • On-site

Full-time

Posted 6 days ago

Job description

At Player 15 Group, we aren't just building a team: we're crafting a legacy.
We're a collective of visionaries who consistently put people first, knowing that true greatness is forged through shared passion and purpose. Service focused to our core, we're driven by an insatiable desire to innovate and elevate every experience. Our strength lies in unity, where diverse talents converge to achieve extraordinary feats, and we infuse every endeavor with genuine joy. Here, a relentless pursuit of growth isn't just encouraged-it's the very air we breathe. If you're ready to transcend expectations, unlock unparalleled potential, and dedicate your energy to something truly special, your moment to make an indelible mark on the future of sports and live entertainment starts now.
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.
    • 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
    • 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
    • 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

The Player 15 Group is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.
Please note this job description is not designed to cover every activity, duty, or responsibility. Duties, responsibilities, and activities may change at any time with or without notice.
For questions about this career opportunity, please contact our People & Culture Recruiting team at recruiting@suns.com

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