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.
Basic qualifications
- 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.
Preferred qualifications
- 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.
Tags & focus areas
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