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Data Science Fall Internship Jobs in Houston, TX

NOV, Inc.

Senior Data Scientist

Houston, TX · On-site

Lead data science initiatives that impact operations globally across multiple business units ... Manage and mentor interns, junior data scientists and analysts * Translate advanced analytics ...

Rice University

Data Scientist

Houston, TX · Hybrid

$110K - $120K/yr

... Fall and Spring terms, with working hours remaining standard Central Time. Per Rice policy 440 ... Bachelor's degree in a relevant field (data science, statistics, social sciences, or related field)

Chevron

2026-2027 Earth Science Intern

Houston, TX · On-site +1

$10K/mo

... data scientists, and/or software developers. Earth Scientists develop technical skills in ... Interns will be provided guidance by a supervisor and a technical mentor. We encourage the ...

Chevron

2026-2027 Earth Scientist Full Time

Houston, TX

$108K - $140K/yr

What's Next After the Internship Topperforming interns may be invited back-or offered a fulltime ... Practical experience with geoscience coding, data science, and/or machine learning. Compensation ...

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Data Science Fall Internship information

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$40

How much do data science fall internship jobs pay per hour?

As of Aug 1, 2026, the average hourly pay for data science fall internship in Houston, TX is $21.49, according to ZipRecruiter salary data. Most workers in this role earn between $16.54 and $23.41 per hour, depending on experience, location, and employer.

What types of projects can I expect to work on during a Data Science Fall Internship?

As a Data Science Fall Intern, you can expect to work on projects involving data cleaning, exploratory data analysis, and the development of predictive models using real-world datasets. Interns often collaborate with full-time data scientists and cross-functional teams to solve business problems, such as improving user engagement, optimizing processes, or generating actionable insights from large data sets. You may also participate in regular team meetings, present findings, and contribute to ongoing research or tool development. This hands-on experience helps you build both technical and communication skills within a dynamic and supportive environment.

What are the key skills and qualifications needed to thrive as a Data Science Fall Intern, and why are they important?

To thrive as a Data Science Fall Intern, you generally need a solid foundation in statistics, programming (often Python or R), and data analysis, typically supported by coursework or experience in computer science, mathematics, or related fields. Familiarity with tools like pandas, scikit-learn, SQL, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help interns interpret data insights and collaborate with team members. These competencies are essential for producing actionable analyses and contributing meaningfully to data-driven projects in a short-term, fast-paced internship environment.

What is a Data Science Fall Internship?

A Data Science Fall Internship is a temporary, structured work experience offered by organizations during the fall semester, designed for students or recent graduates interested in data science. Interns typically work on real-world projects involving data collection, analysis, machine learning, and visualization under the guidance of experienced data scientists. This internship provides hands-on experience, exposure to industry tools and techniques, and helps participants build valuable skills for future careers in data science. It also offers networking opportunities and a chance to explore potential career paths within the field.

What is the difference between Data Science Fall Internship vs Data Analyst Intern?

AspectData Science Fall InternshipData Analyst Intern
Required CredentialsEnrolled in or recent graduate of a related field (e.g., Data Science, Computer Science, Statistics)Enrolled in or recent graduate of a related field (e.g., Data Analysis, Business, Statistics)
Work EnvironmentTech companies, startups, research labs, often collaborative and project-basedBusiness firms, consulting agencies, often focused on reporting and data visualization
Employer & Industry UsageUsed by tech firms, finance, healthcare, and academia for entry-level talentCommon in corporate, marketing, and consulting sectors for supporting decision-making

The Data Science Fall Internship and Data Analyst Intern roles share similarities in required education and work environment but differ in focus. Data Science internships emphasize machine learning, programming, and statistical modeling, while Data Analyst internships focus more on data visualization, reporting, and business insights. Both are valuable entry points into data careers, often overlapping in skills but serving different industry needs.

What are popular job titles related to Data Science Fall Internship jobs in Houston, TX? For Data Science Fall Internship jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Data Science Fall Internship jobs in Houston, TX look for? The top searched job categories for Data Science Fall Internship jobs in Houston, TX are:
What cities near Houston, TX are hiring for Data Science Fall Internship jobs? Cities near Houston, TX with the most Data Science Fall Internship job openings:
Data Science Fall Internship jobs near you
Infographic showing various Data Science Fall Internship job openings in Houston, TX as of July 2026, with employment types broken down into 11% Internship, 41% Full Time, 32% Part Time, and 16% Temporary. Highlights an 100% In-person job distribution, with an average salary of $44,701 per year, or $21.5 per hour.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Houston, TX

Full-time

Posted 11 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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