What are the responsibilities and job description for the Data Scientist - Enterprise AI position at Chevron?
Chevron is accepting online applications for the position Data Scientist - Enterprise AI through January 20, 2026 at 11:59 p.m. (Central Time).
Join Chevron’s Enterprise AI team to shape the future of intelligent decision-making and AI transformation for the company. As a data scientist, you will apply machine learning, optimization methods, advanced analytics to deliver impactful insights and AI-driven products across Chevron’s key strategic initiatives.
This role is ideal for scientists passionate about data-driven innovation, modern AI architectures, and solving complex business challenges through rigorous modeling and experimentation. You will design and deploy scalable, production-ready models, architect solutions with a holistic AI foundation, and create reusable analytical assets that accelerate Chevron’s AI strategy.
Key Responsibilities
Relocation may be considered.
International Considerations
Expatriate assignments will not be considered.
Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position.
Join Chevron’s Enterprise AI team to shape the future of intelligent decision-making and AI transformation for the company. As a data scientist, you will apply machine learning, optimization methods, advanced analytics to deliver impactful insights and AI-driven products across Chevron’s key strategic initiatives.
This role is ideal for scientists passionate about data-driven innovation, modern AI architectures, and solving complex business challenges through rigorous modeling and experimentation. You will design and deploy scalable, production-ready models, architect solutions with a holistic AI foundation, and create reusable analytical assets that accelerate Chevron’s AI strategy.
Key Responsibilities
- Architect AI Solutions:Identify, frame, and design advanced analytics and AI solutions—including agentic AI systems, predictive models, and optimization algorithms—to improve decision-making, workflow automation, and operational efficiency.
- Develop and Deploy Models:Build, test, and operationalize machine learning models and data science products using primarily AzureML, DataRobot, Databricks, while maintaining flexibility to leverage other services as business needs evolve. Ensure solutions are scalable, future-proofed, and aligned with the enterprise AI best practices.
- Enable Reusable AI Assets:Create modular, reusable feature stores, model components, and pipelines that support multiple AI applications and accelerate delivery across the enterprise.
- Collaborate Across Disciplines:Work closely with AI delivery teams, including software engineers, AI engineers, and applied scientists, to integrate models into production systems and/or agentic AI workflows.
- Data Preparation and Feature Engineering:Source, clean, and transform structured and unstructured data for modeling, leveraging Databricks, Spark, AzureML, and advanced feature engineering techniques.
- Model Lifecycle Management:Establish robust model governance, monitoring, and retraining processes to ensure reliability, fairness, and compliance throughout the model lifecycle.
- Innovation and Continuous Learning:Stay ahead of emerging trends in AI/ML, generative AI, and agentic systems, applying cutting-edge techniques to Chevron’s most critical business challenges.
- Bachelor’s degree and Master’s degree in computer science, mathematics, statistics, data science, or a related quantitative field in engineering and able to demonstrate high proficiency in programming fundamentals.
- 5 years of experience in applying analytics and machine learning in enterprise environments
- Hands-on experience with Microsoft Azure and tools in its ecosystem
- Strong proficiency in Python with experience in ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch, etc.)
- Deep understanding of statistical modeling, optimization, and data mining techniques
- Ability to engage business and technical experts at all organizational levels and assess opportunities to apply data science analytics to improve their workflows, and deliver information and insight to support business decisions
- Ability to build collaborative relationships across functional and geographic areas to plan, facilitate, and develop advanced analytics solutions for key Chevron’s key business units and functions.
- Experience with agentic AI architectures, generative AI, and reinforcement learning.
- Familiarity with MLOps, CI/CD for ML, AzureDevOps, Git, and model deployment in Azure environments.
- Knowledge of oil and gas industry workflows (upstream, downstream, supply & trading, and corporate functions).
- Strong technical leadership and mentoring capabilities.
Relocation may be considered.
International Considerations
Expatriate assignments will not be considered.
Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position.