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Internship Nba Computer Science Jobs in Houston, TX

Danaher

Software Automation Internships

Houston, TX · On-site

... Computer Science, or another hard science Preference for students who have completed at least 3 years of academic coursework by internship start * Experience with hands-on lab testing and technical ...

Danaher

Software Engineer Internships

The Woodlands, TX · On-site

... in Computer Science, Software Engineering, Biomedical Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship ...

Danaher

Software Engineer Internships

Houston, TX · On-site

... in Computer Science, Software Engineering, Biomedical Engineering (with computational focus), or related field * Preference for students who have completed 3+ years of coursework by the internship ...

Sycamore Life Sciences, LLC

Be Seen First

Software Engineer Intern

Houston, TX · On-site

$15 - $18/hr

Internship About the Role Sycamore Life Sciences is seeking a motivated and curious Computer Software Engineer Intern to support the development of internal tools, automation workflows, and ...

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Internship Nba Computer Science information

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.

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.

Internship Nba Computer Science jobs near you
Infographic showing various Internship Nba Computer Science job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 3% Contract, and 1% Nights. Highlights an 80% Physical, 1% Hybrid, and 19% Remote job distribution.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Houston, TX • On-site

Full-time

Posted 26 days ago

Job description

Application Deadline: September 1, 11:59pm EST

Program Summary - Commercial Technology Internships

Company Overview:

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.

Position Overview:

CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.

Responsibilities:

  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:

  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.

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