2025-2026: Information Technology – Information and Analytics – Full Time (Previous Intern)
Houston, Texas, United States of America
Internship
Hybrid
$91K/yr - $129K/yr
Intern, Entry Level
Chevron Corporation is an integrated energy and technology company that believes affordable, reliable, and ever-cleaner energy is essential to achieving a more prosperous and sustainable world. They are seeking motivated individuals for various roles in Information Technology – Information and Analytics, where the main purpose is to leverage data science, machine learning, and data engineering to support strategic business objectives and improve decision-making.
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
Required
Must be currently enrolled in a four-year college or university and classified as a senior or graduate student with anticipation of receiving a bachelor’s or master’s degree by July 2025; OR college graduates with less than two years’ experience since receiving a degree.
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: Experience developing cloud first solutions using Microsoft Azure Services (Azure Functions, Azure App Services, Azure Event hubs, Azure SQL DB, Azure Synapse etc.)
Bachelor’s or master’s degree in Computer Science, 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.
Benefits
Competitive pay
Cash incentives
Flexible benefit programs
Flexible work schedules
Every other Friday off
Remote work where approved
Health care coverage
Retirement plan
Protection coverage
Time off and leave programs
Training and development opportunities
Chevron Corporation is an integrated energy and technology company that believes affordable, reliable, and ever-cleaner energy.
