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Chevron · 5 months ago

2025-2026 Information Technology – Information and Analytics – Intern

Houston, Texas, United States of America

Internship

Onsite

Intern

$23/hr - $46/hr

Chevron is a leading energy company committed to advancing a lower-carbon economy. They are seeking interns in Information Technology – Information and Analytics to support data-driven decision-making and strategic business objectives by applying data science and analytics expertise across various roles.

EnergyFossil FuelsGeothermal EnergyManufacturingNatural ResourcesOil and GasRenewable Energy

No H1B

Responsibilities

Identify and frame opportunities to apply advanced analytics, modeling, and related technologies to data that provide insight and improve decision making, and automation

Identify data necessary and appropriate technology to solve business challenges

Clean data, develop models, and test models

Establish the life cycle management process for models

Provide technical mentoring in modeling and analytics technologies, the specifics of the modeling process, and general consulting skills

Identify, acquire, cleanse/prepare, store data, and develop reusable data products aligned with defined architecture patterns

Create and manage data pipelines that enable advanced analytics models, and handle data challenges and opportunities

Ensure the scalability and reliability of model deployment, and document the technical aspects of the process

Develop and share reusable tools for data engineering tasks, and leverage technical services to optimize data workflows

Consult, identify and frame opportunities to implement AI solutions that help gain insight and improve decision making and automation

Identify data, technology, and architectural design patterns to solve business challenges using analytical tools and AI design patterns and architectures

Partner with Data Scientists and Chevron IT Foundational services to implement complex algorithms and models into enterprise scale machine learning pipelines

Build machine and deep learning systems optimized for scalability and performance

Transform data science prototypes into scalable solutions in a production environment

Orchestrate and configure infrastructure that assists Data Scientists and analysts in building low latency, scalable and resilient machine learning, and optimization workloads into an enterprise software product

Run machine learning experiments and fine-tune algorithms to ensure optimal performance

Access, gather, and analyze data from source systems

Help frame the business problem by providing quantitative and qualitative data analysis (data quality, availability, etc.)

Drive insights to business problems by visualizing the data and telling a story through data (report patterns, trends, anomalies, etc.)

Participate in the end-to-end product development lifecycle as a member of agile team

Contribute to data analysis, data wrangling, data visualization, and acceptance testing

Present findings and new development to help refine backlog items

Understand the business use of data and stakeholder requirements to support strategic business objectives

Collaborate with delivery teams to provide data management direction and support for initiatives and product development

Contribute to the design of common information models

Consult on the appropriate data integration patterns, data modeling and data quality

Maintain and share knowledge of requirements, key data types and data definitions, data stores, and data creation process

Qualification

Data ScienceMachine LearningData EngineeringData AnalysisSQLPythonData ModelingData QualityCommunication SkillsCollaboration

Required

Must provide a current, unofficial transcript with online resume (as proof of good academic standing) when applying for this position to be considered

Data acquisition, analysis, modeling, movement, transformation, and preparation experience

Demonstrated depth in advanced analytics / data science technologies (e.g., machine learning, operations research, statistics, data mining)

Data Analyst: Experience with data modeling, data management, data quality, SQL

Data Engineer: Experience using data pipelines, Data Lake and storage configuration, Python, RDBMS & SQL

Machine Learning Engineer: Software Engineering background. Working knowledge of mathematics (primarily linear algebra, probability, statistics), and algorithms. Working knowledge of machine learning frameworks and machine learning libraries

Preferred

Currently enrolled in bachelor's or master's degree program in Computer Science, Computer Engineering, Mathematics, Statistics, Operations Research, Data Science, Management Information Systems, or related Engineering degree

Ability to communicate in a clear and concise manner both orally and in writing

Knowledge of enterprise SaaS complexities including security/access control, scalability, high availability, concurrency, online diagnoses, deployment, upgrade/migration, internationalization, and production support

Experience designing custom APIs for machine learning models for training and inference processes

Software engineering skills and fundamentals: coding (Python, R) and Github, source control versioning, requirement spec, architecture, and design review, testing methodologies, CI/CD, etc