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Nba Data Science Jobs (NOW HIRING)

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$160K/yr

Knowledge of data science and machine learning concepts * A strong interest in sports and sports betting, with an emphasis on Tennis. An understanding of US-based sports including the NFL, NBA, MLB ...

Swish Analytics

Data Engineer

San Francisco, CA · Remote

$160K/yr

Knowledge of data science and machine learning concepts * A strong interest in sports and sports betting, with an emphasis on Tennis. An understanding of US-based sports including the NFL, NBA, MLB ...

2K

Staff Data Analyst

Novato, CA · On-site

... NBA 2K, one of the top-selling franchises in the world, and legendary titles like BioShock ... Game Science & Insights team, to explore, analyze, report, and action on data from our portfolio of ...

2K

Staff Data Analyst

Novato, CA · On-site

... NBA 2K , one of the top-selling franchises in the world, and legendary titles like BioShock ... Game Science & Insights team, to explore, analyze, report, and action on data from our portfolio of ...

Cacheflow

Enterprise Data Scientist

San Francisco, CA · On-site

$160 - $260/hr

... NBA star Stephen Curry. Why Kikoff This is a consumer fintech startup, and you will be working with ... Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field * A ...

Minerva

Staff Data Engineer

Manhattan, NY · On-site

$200 - $250/hr

We've raised $20M from The General Partnership, 8VC, Lingotto, NBA Investments, Topology Ventures ... Data Scientist (ADS) build models on top of it. You own the substrate they stand on (the contracts ...

New

2K

Staff Data Analyst

Novato, CA · On-site

... NBA ® 2K, one of the top-selling franchises in the world, and legendary titles like BioShock ® ... Game Science & Insights team, to explore, analyze, report, and action on data from our portfolio of ...

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Nba Data Science information

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How much do nba data science jobs pay per year?

As of Aug 20, 2026, the average yearly pay for nba data science in the United States is $109,108.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $155,500.00 per year, depending on experience, location, and employer.

What is an NBA Data Science job?

An NBA Data Science job involves using statistical modeling, machine learning, and data analysis to evaluate player performance, optimize team strategies, and improve decision-making in basketball operations. Professionals in this role work with large datasets, including player tracking data, game statistics, and biomechanics, to extract actionable insights. They collaborate with coaches, front-office staff, and analysts to enhance scouting, game tactics, and player development. Strong programming skills in Python or R, along with expertise in data visualization and predictive modeling, are essential for success in this field.

What does an NBA Data Science professional do?

As an NBA Data Science professional, your day-to-day work often involves cleaning and analyzing large datasets on player performance, in-game events, and scouting information. You will develop predictive models, create data visualizations, and interpret statistical results to support coaching staff and front-office decision-makers. Collaboration with coaches, video analysts, and other departments is common, as you will help translate data into actionable insights. Additionally, you'll stay up to date with the latest advancements in basketball analytics and may be asked to present findings in meetings or reports. The role is dynamic and impactful, offering opportunities to influence game strategy and long-term team development.

What are the key skills and qualifications needed to thrive in the NBA Data Science position?

To thrive in NBA Data Science, you need strong analytical skills, expertise in statistics, programming proficiency (usually in Python or R), and a deep understanding of basketball data and metrics, typically supported by a degree in statistics, computer science, mathematics, or a related field. Familiarity with data visualization tools, SQL databases, and machine learning frameworks is highly valued, and additional certifications in data science or analytics are beneficial. Effective communication, teamwork, and problem-solving skills set standout candidates apart, as the role requires translating complex data insights for coaches, managers, and other non-technical stakeholders. These skills are essential to drive data-informed decision-making that can impact team strategy and player performance within a fast-paced NBA environment.

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Nba Data Science jobs near you
Infographic showing various Nba Data Science job openings in the United States as of August 2026, with employment types broken down into 85% Full Time, and 15% Part Time. Highlights an 85% In-person, and 15% Remote job distribution, with an average salary of $109,108 per year, or $52.5 per hour.

Data Engineer

Swish Analytics

San Francisco, CA • On-site, Remote

$160K/yr

Full-time

Re-posted yesterday

Job description

Company Overview
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Job Description
The Swish Analytics team is seeking Data Engineers to have a direct impact on the infrastructure and delivery of our core consumer and enterprise data offerings as well as helping support our coverage of non-US sports. We're a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.
Duties
  • Support production systems and help triage issues during live sporting events
  • Architect low-latency, real-time analytics systems including raw data collection, feature development and endpoint production
  • Build new sports betting data products and predictions offerings
  • Integrate large and complex real-time datasets into new consumer and enterprise products
  • Develop production-level predictive analytics into enterprise-grade APIs
  • Contribute to the design and implementation of new, fully-automated sports data delivery frameworks

Requirements
  • BS/BA degree in Mathematics, Computer Science, or related STEM field
  • Minimum of 2+ years of demonstrated experience writing production level code (Python)
  • Proficiency in Python and SQL (preferably MySQL) Demonstrated experience with Airflow
  • Demonstrated experience with Kubernetes
  • Experience building end-to-end ETL pipelines
  • Experience utilizing REST APIs
  • Experience with version control (git), continuous integration and deployment, shell scripting, and cloud-computing infrastructures (AWS)
  • Experience with web scraping and cleaning unstructured data
  • Knowledge of data science and machine learning concepts
  • A strong interest in sports and sports betting, with an emphasis on Tennis. An understanding of US-based sports including the NFL, NBA, MLB, NHL, College Football, College Basketball, and the ability use your knowledge of the sport to inform your work with complex datasets

Base Salary: Starting at $160,000 - DOE
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Data Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

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