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Summer Basketball Data Analyst Jobs (NOW HIRING)

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Data Analyst

Manhattan, NY · On-site

$70K - $90K/yr

  • Medical

  • Retirement

  • PTO

... Summer Fridays, catered lunches, a fully stocked kitchen, ZogSports teams, happy hours and ... Department Product Role Data Analyst Locations New York Yearly salary $70,000 - $90,000

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Summer Basketball Data Analyst information

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$34K

$82.6K

$136K

How much do summer basketball data analyst jobs pay per year?

As of Aug 17, 2026, the average yearly pay for summer 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 skills and qualifications are needed to thrive as a summer basketball data analyst?

To thrive as a Summer Basketball Data Analyst, you need strong analytical skills, a background in statistics or mathematics, and familiarity with basketball analytics concepts, typically supported by a relevant degree or coursework. Proficiency in data analysis tools such as Excel, SQL, R, or Python, as well as experience with basketball data platforms like Synergy Sports or Second Spectrum, is commonly required. Excellent communication, attention to detail, and teamwork are important soft skills for conveying insights and collaborating with coaches or staff. These skills ensure accurate analysis and effective communication, directly supporting team strategy and player development during the summer season.

What does a summer basketball data analyst do?

As a Summer Basketball Data Analyst, you can expect to work on projects such as collecting and cleaning game statistics, analyzing player performance trends, and developing visual dashboards to present insights to coaching staff. You may also be responsible for tracking advanced metrics, preparing pre-game reports, and collaborating closely with coaches and other analysts to inform strategy decisions. The fast-paced environment means you'll need to adapt quickly to new data and provide actionable insights on tight deadlines.

What is the difference between Summer Basketball Data Analyst vs Summer Basketball Coach?

AspectSummer Basketball Data AnalystSummer Basketball Coach
Required CredentialsDegree in sports management, statistics, or related field; proficiency in data analysis toolsCoaching certifications, experience in basketball coaching, and knowledge of game strategies
Work EnvironmentOffice settings, sports analytics labs, or on-site at basketball campsOn-court coaching, training sessions, and team management during summer programs
Employer & Industry UsageSports teams, analytics firms, or youth sports organizationsSchool teams, summer sports camps, and youth basketball leagues
Common Search & ComparisonYesNo

The Summer Basketball Data Analyst focuses on analyzing player and team performance data to inform strategies, often working behind the scenes. In contrast, the Summer Basketball Coach directly trains and manages players during summer programs. While both roles are involved in basketball, their responsibilities, skills, and work environments differ significantly.

What is a summer basketball data analyst?

Summer Basketball Data Analysts are professionals who collect, process, and interpret basketball-related data during the summer season, often supporting teams, camps, or leagues. They analyze player and team statistics, track performance metrics, and provide insights to coaches and staff to enhance decision-making and improve outcomes. These analysts use statistical software and data visualization tools to present their findings. Their work helps identify trends, assess player development, and inform strategies for both training and games.
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What are the most commonly searched types of Basketball Data Analyst jobs?

The most popular types of Basketball Data Analyst jobs are:

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Summer Basketball Data Analyst jobs near you
Infographic showing various Summer Basketball Data Analyst job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% 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 25 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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