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Internship Nba Computer Science Jobs in California

Mentorship & Learning Interns will work closely with experienced staff and technical mentors with expertise in: * Computer Science * Data Science & Analytics * Applied AI & Machine Learning

During the internship, you will support the Data team by analyzing data, building models ... Computer Science * Data Science * Statistics * Mathematics * Engineering * Economics * Physics * Or ...

During the internship, you will support the Data team by analyzing data, building models ... Computer Science * Data Science * Statistics * Mathematics * Engineering * Economics * Physics * Or ...

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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:
What cities in California are hiring for Internship Nba Computer Science jobs? Cities in California with the most Internship Nba Computer Science job openings:
Applied Data Science Intern

Applied Data Science Intern

Evolver

Palo Alto, CA

Other

Re-posted 28 days ago


Job description

Applied Data Science Summer Internship 

About Us:

Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In just 1.5 years, the company has grown from 0 to nearly 100 employees, bringing together an exceptional team of technologists, researchers, and industry experts. Founders includes former executives from some of the world's top organizations, including the former Global CTO and Global Board Member of Ernst and Young and the former VP of AI from Microsoft, alongside senior leaders from other major global enterprises. The team includes multiple PhDs and a strong concentration of employees with advanced degrees from leading universities. This in-person internship offers a small cohort of students the opportunity to work directly alongside experienced operators and AI experts while gaining hands-on exposure to using the latest innovations in data science applications at a frontier startup environment.

Program Details:

Evolver is launching a small, highly selective summer internship cohort for students and emerging talent to gain hands-on experience applying data science techniques to enterprise datasets while learning to leverage and deploy AI systems for real-world Fortune 500 business use cases.

This is an intensive 10-week, full-time small cohort program designed to provide direct mentorship from experienced professionals in computer science, data science, artificial intelligence, and enterprise software deployment.

  • Duration: 10 weeks (full-time), June through Early August.
  • Competitive Compensation: Tailored to your experience and skill set.
  • Format: Hybrid (4+ days in person) - Based in Palo Alto, CA off University Ave
  • Cohort Size: Small and mentorship-focused
  • Learning Goals: Develop and apply AI-driven data science solutions on real-world datasets and workflows supporting Fortune 500 enterprise use cases.

Role Details:

Interns will contribute to real data innovation projects involving:

  • Data analysis and machine learning pipelines
  • AI agents, retrieval systems, and evaluation frameworks
  • Enterprise AI integration and deployment tooling
  • Product prototyping and applied research
  • Automation systems for large-scale organizational use
  • Real world enterprise use cases of graph theory
  • Gain direct exposure to Fortune 500 clients
  • Access enterprise-scale AI and data science initiatives through hands-on collaboration with internal teams and customer engagements.

Projects are oriented toward practical AI solutions deployed in enterprise and Fortune 500 environments.

Mentorship & Learning

Interns will work closely with experienced staff and technical mentors with expertise in:

  • Computer Science
  • Data Science & Analytics
  • Applied AI & Machine Learning
  • Enterprise Infrastructure
  • Scalable AI Deployment
  • Risk and Compliance Frameworks
  • Tax and Audit

The program is structured as a high-engagement cohort-based apprenticeship experience emphasizing:

  • Daily in person technical collaboration
  • Rapid learning and iteration
  • Exposure to real deployment challenges
  • Cross-disciplinary problem solving
  • Professional development in AI engineering and enterprise systems

Who Should Apply:

We welcome applications from:

  • Graduate students with a record of excellence
  • Exceptional advanced undergraduates

All candidates are required to be recommended by an accredited professor leading a relevant program at a top university. Will be verified during application process.

Strong candidates typically demonstrate:

  • Programming experience
  • Curiosity about AI systems and emerging technologies
  • Initiative, creativity, and strong problem-solving ability
  • Prior technical, research, or project experience

You do not need deep expertise in every area, we value intellectual curiosity, adaptability, and motivation to build.