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Basketball Data Jobs (NOW HIRING)

DB Data Hoops Scouting

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Basketball Sales Rep

Atlanta, GA · Remote

$1.0K - $3.0K/mo

Basketball Sales Representative Company ... Data Hoops Scouting Position: Sales Representative Job Type: Independent Contractor / Commission ...

DB Data Hoops Scouting

Be Seen First

Basketball Sales Rep

Atlanta, GA · Remote

$1.0K - $3.0K/mo

Basketball Sales Representative Company ... Data Hoops Scouting Position: Sales Representative Job Type: Independent Contractor / Commission ...

Zeta Charter Schools

Basketball Instructor

New York, NY · On-site

$2.5K/wk

Use data-driven approaches and teaching resources to drive student achievement * Develop authentic ... Lead a strong after-school Basketball program that furthers students' passion and skill set, and ...

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How much do basketball data jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for basketball data in the United States is $15.45, according to ZipRecruiter salary data. Most workers in this role earn between $13.22 and $16.83 per hour, depending on experience, location, and employer.

What is a basketball data analyst?

A Basketball Data Analyst is a professional who collects, processes, and interprets data related to basketball games, players, and teams. They use statistical methods and software tools to analyze performance, identify trends, and provide insights that help coaches, players, and management make informed decisions. Their work often includes breaking down player statistics, evaluating team strategies, and supporting scouting or recruitment. By leveraging data, they contribute to improving team performance and competitive advantage. This role is increasingly important in both professional leagues and collegiate basketball.

What skills and qualifications are needed to thrive as a basketball data analyst?

To thrive as a Basketball Data Analyst, you need strong quantitative and statistical analysis skills, knowledge of basketball analytics, and typically a degree in statistics, mathematics, data science, or a related field. Familiarity with data analysis tools such as Python, R, SQL, and basketball-specific software like Synergy or SportVU is crucial. Attention to detail, problem-solving ability, and effective communication help translate complex data into actionable insights for coaches and teams. These skills are vital for driving strategic decisions and enhancing team performance through data-driven analysis.

What are common challenges faced by professionals working in basketball data analysis, and how can they be addressed?

Professionals in basketball data analysis often encounter challenges such as managing large volumes of complex data, keeping up with rapidly evolving analytical tools, and ensuring their insights are actionable for coaches and teams. Effective collaboration with coaching staff and athletes is crucial to translate statistical findings into practical strategies. To address these challenges, analysts should stay updated on the latest analytics software, develop strong communication skills, and build collaborative relationships with team members to ensure their work directly supports on-court performance.

What is the difference between Basketball Data vs Basketball Analyst?

AspectBasketball DataBasketball Analyst
Required CredentialsData analysis skills, familiarity with sports data toolsBasketball knowledge, data analysis skills, communication abilities
Work EnvironmentData teams, sports organizations, analytics firmsSports teams, media outlets, consulting firms
Industry UsageCollecting, managing, and processing basketball dataInterpreting data to provide insights and strategies

Basketball Data focuses on gathering and managing basketball-related data, while Basketball Analysts interpret this data to provide strategic insights. Both roles require analytical skills, but Analysts also need strong communication abilities to present findings effectively.

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What states have the most Basketball Data jobs?

States with the most job openings for Basketball Data jobs include:

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The top searched job categories for Basketball Data jobs are:

Basketball Data jobs near you
Infographic showing various Basketball Data job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, 42% Part Time, and 8% Temporary. Highlights an 100% In-person job distribution, with an average salary of $32,133 per year, or $15.4 per hour.

Basketball Data Scientist, Phoenix Suns

Player 15 Group

Phoenix, AZ • On-site

Full-time

Re-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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