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Internship Nba Computer Science Jobs in California

Faire

Data Science Intern

San Francisco, CA · On-site

$75/hr

Data Science Internship - Fall 2026 Faire leverages machine learning and data insights to transform ... in Computer Science, Operations Research, Statistics, Econometrics, or a related technical ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics ... internships, or research projects). * Demonstrated experience developing generative AI solutions ...

LLNL

Data Science Engineer

Livermore, CA

$121K - $154K/yr

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics ... internships, or research projects). * Demonstrated experience developing generative AI solutions ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$9.7K/wk

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics ... internships, or research projects). * Demonstrated experience developing generative AI solutions ...

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All JobsNba Computer Science JobsInternship Nba Computer Science JobsInternship Nba Computer Science Jobs in California

Internship Nba Computer Science information

What NBA player studied computer science?

One NBA player who studied computer science is Chris Bosh, who earned a degree in the field from Georgia Tech. Some players pursue degrees in computer science or related fields to prepare for careers beyond basketball or to develop skills in technology and data analysis.

What types of projects can I expect to work on during an NBA Computer Science internship?

As an NBA Computer Science intern, you'll typically be involved in projects that support data analysis, software development, or technology integration for basketball operations, fan engagement, or business analytics. You may collaborate with data scientists, software engineers, and business analysts to develop tools, analyze large datasets, or improve internal systems. The NBA values innovation, so you might also work on pilot programs using emerging technologies. This collaborative environment provides valuable exposure to real-world applications of computer science in the sports industry.

Which internship is best for a CS student?

The best internship for a CS student depends on their interests and career goals, but competitive programs often include those at major tech companies, research labs, or startups that offer hands-on experience with coding, software development, and project collaboration. Relevant skills such as programming languages, data structures, and teamwork are important, and internships that provide mentorship and real-world projects are highly valuable for career development.

How much do NBA interns get paid?

NBA interns typically receive stipends that can range from around $15 to $20 per hour, depending on the role and location. Compensation may also include other benefits such as networking opportunities and exposure to professional sports environments, with schedules often requiring full-time commitment during the internship period.

What is an NBA Computer Science internship?

An NBA Computer Science internship is a temporary position offered by the National Basketball Association (NBA) or its affiliated teams and organizations to students or recent graduates pursuing a degree in computer science or a related field. Interns typically work on projects involving software development, data analysis, and technology solutions that support basketball operations, fan engagement, or business analytics. These internships provide hands-on experience in applying computer science skills to real-world sports industry challenges and may involve working with big data, machine learning, or developing digital products. Interns often collaborate with professionals in IT, analytics, and basketball operations, gaining valuable insights and networking opportunities within the sports and technology sectors.

What is the difference between Internship Nba Computer Science vs Data Analyst?

AspectInternship Nba Computer ScienceData Analyst
Required CredentialsRelevant coursework, basic programming skillsDegree in statistics, data science, or related field
Work EnvironmentSports industry, tech teams, NBA officesVarious industries, corporate offices, data teams
Employer & Industry UsageNBA teams, sports tech companiesBusinesses across sectors like finance, marketing, sports
Common Search & ComparisonInternship opportunities, sports tech rolesData analysis roles, business intelligence

Internship Nba Computer Science focuses on gaining experience in sports tech and programming within the NBA environment, often requiring basic coding skills and a passion for sports. Data Analysts analyze data to inform business decisions across industries. While both roles involve data and technical skills, internships are entry-level and industry-specific, whereas Data Analysts work across various sectors with more specialized data analysis expertise.

How to get an internship with the NBA?

To secure an internship with the NBA, candidates should have a strong background in computer science, programming skills, and familiarity with data analysis tools. Applying through the NBA's official careers website, networking within the sports industry, and gaining relevant experience or certifications can improve chances. Internships typically require a current student status and a demonstrated interest in sports technology or analytics.
What are the most commonly searched types of Nba Computer Science jobs in California? The most popular types of Nba Computer Science jobs in California are:
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Internship Nba Computer Science jobs near you
Data Science Intern

Data Science Intern

Faire

San Francisco, CA • On-site

$75/hr

Other

Re-posted 3 days ago

Job description

Data Science Internship - Fall 2026

Faire leverages machine learning and data insights to transform the wholesale industry, giving independent retailers the tools to compete with large-scale e-commerce platforms and big-box stores. Our Data Science team builds and maintains the algorithmic systems - spanning search, personalization, recommendation, and ranking - that power our marketplace and help our customers thrive.

We are hiring Data Science interns across several teams and are looking for intellectually curious, self-directed problem solvers eager to work end-to-end on high-impact challenges, from data exploration to production-ready solutions.

Our internships are paid, 12-14 weeks in duration, with flexible start dates. Extensions are considered based on project scope and mutual interest.

Open Team

Search & Recommendation

  • Design and deploy state-of-the-art recommender systems that power ranking and discovery across the marketplace
  • Develop rich user and item representations through embeddings, sequence models, and graph-based methods
  • Build real-time and streaming data pipelines that enable dynamic, context-aware personalization at scale
  • Apply exploration-exploitation strategies - including contextual bandits and reinforcement learning - to optimize recommendations under uncertainty
  • Advance recommendation quality through improvements to diversification, novelty, and long-term user engagement
  • Own the full ML lifecycle: from problem formulation and modeling through offline evaluation and online experimentation

What You'll Do

  • Design, develop, and A/B test cutting-edge machine learning algorithms and analytical solutions, with guidance from senior technical leads
  • Communicate project objectives, methodologies, and results clearly to both immediate teammates and broader cross-functional stakeholders
  • Navigate the complexity of a two-sided marketplace, identifying and addressing the unique challenges that arise at the intersection of retailer and brand needs

What We're Looking For

All candidates must be currently enrolled or recently graduated Master's or PhD students in Computer Science, Operations Research, Statistics, Econometrics, or a related technical discipline. Beyond that, we're looking for team-specific experience:

Search & Recommendation Systems

  • Publications or submissions to top-tier venues such as KDD, RecSys, ICML, NeurIPS, WWW, or SIGIR
  • Experience with recommender systems (collaborative filtering, deep recommenders, ranking), representation learning and embeddings, sequential models (RNNs, Transformers for user behavior modeling), bandit and reinforcement learning methods, and large-scale retrieval and ranking systems
  • Familiarity with offline evaluation metrics (NDCG, MAP, recall) and online experimentation
  • Experience working with large-scale or production datasets

Pay rate:

San Francisco: the pay rate for this role is $75 USD per hour.

Actual hourly pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

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