Data & Analytics Engineer – Houston

Position Summary

Data roles are available in the Information Technology family in Information & Analytics. Positions include Data Scientist, Data Engineer, Machine Learning Engineer, Business Intelligence Analyst, and Data Analyst. All roles support data‑driven decisions and infrastructure across the enterprise.

Houston, TX

Key responsibilities:

• Partner with business to identify opportunities to apply data science and create data science products that deliver strong value.
• Identify and frame opportunities to apply advanced analytics, modeling, and related technologies to 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.

Key responsibilities:

• 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.
• Ensure the scalability and reliability of model deployment and document the technical aspects.
• Develop and share reusable tools for data engineering tasks.
• Leverage technical services to optimize data workflows.

Key responsibilities:

• Consult, identify and frame opportunities to implement AI solutions that improve decision making and automation.
• Identify data, technology, and architectural design patterns to solve business challenges.
• Partner with Data Scientists and IT Foundational services to implement algorithms and models at enterprise scale.
• Build machine and deep learning systems optimized for scalability and performance.
• Transform data science prototypes into scalable solutions in production.
• Orchestrate and configure infrastructure to support low‑latency, scalable machine learning workloads.

Key responsibilities:

• Access, gather, and analyze data from source systems.
• Help frame the business problem through quantitative and qualitative data analysis.
• Drive insights by visualizing data and telling a data story.
• Participate in the end‑to‑end product development lifecycle as part of an agile team.
• Contribute to data analysis, wrangling, visualization, and acceptance testing.
• Present findings to refine backlog items.

Key responsibilities:

• Understand business use of data and stakeholder requirements.
• Collaborate with delivery teams to support initiatives and product development.
• Consult on data integration patterns, data modeling, and data quality.
• Maintain knowledge of data types, definitions, stores, and creation processes.

• Preferred education:
  
  Bachelor’s or master’s degree in Computer Science, Mathematics, Statistics, Operations Research, Data Science, Management Information Systems, or a related engineering degree.
• For students: must be currently enrolled as a senior or graduate student with anticipated graduation by July
  2025; or a college graduate with less than two years’ experience.
• Proof of good academic standing: current unofficial transcript and resume.
• Experience:
  
  data acquisition, analysis, modeling, transformation, and preparation.
• Advanced analytics/data science technologies: machine learning, operations research, statistics, data mining.
• Data Engineer – pipelines, Data Lake, storage configuration, Python, RDBMS & SQL.
• Machine Learning Engineer – cloud‑first solutions using Microsoft Azure services (Functions, App Services, Event Hubs, SQL DB, Synapse, etc.) and ML frameworks/libraries (MLFlow, Kubeflow, Tensor Flow, Keras, scikit‑learn, PyTorch, Num Py, Sci Py).
• Communication: clear, concise written and oral communication.
• Enterprise SaaS knowledge: security/access control, scalability, high availability, concurrency, deployment, migration, internationalization, production support.
• Custom API design for machine learning models and standard software engineering practices (Python, R, Git Hub, CI/CD, testing).

The compensation range for this position is $94,000–$110,000 annually. Chevron offers competitive variable pay, health care coverage, retirement and protection plans, time off, leave programs, training and development opportunities, and allowances related to specific work situations.

Chevron is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, sex (including pregnancy), sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by law. We are committed to providing reasonable accommodations for qualified individuals with disabilities.