GenAI Data Scientist, Commercial, Supply Chain & Trading

GenAI Data Scientist, Commercial, Supply Chain & Trading

Location:

Spring, TX, US, 77389

Company:
Exxon Mobil Technology and Engineering Company

At Exxon Mobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.

The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.

We invite you to bring your ideas to Exxon Mobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we can work together.

• Work on complex AI use cases from ideation and discovery through deployment and sustainment as part of integrated, enterprise-level teams.
• Collaborate with Exxon Mobil subject matter experts to strengthen organizational capabilities in AI/ML.
• Support business teams in making impactful, data-driven decisions.

• Lead the scoping, design, development, and deployment of AI/ML solutions, primarily focused on Generative AI applications for subsurface and well-related operations.
• Collaborate with data and machine learning engineers to operationalize models and ensure seamless integration with existing digital infrastructure.
• Build and deploy AI system components (such as chatbots, agents, and other workflow automation components) capable of interacting with diverse data sources and providing insightful information to users.
• Develop and implement solutions involving orchestration of multiple AI agents to achieve complex tasks.
• Apply domain knowledge and physical principles to improve model accuracy and reliability.
• Contribute to the growth of internal AI capabilities by sharing expertise and developing best practices.
• Provide technical mentorship and guidance to colleagues across teams.
• Work closely with team leads and subject matter experts to align on project priorities, strategy, and solution design.
• Optimize end to end AI solutions to enhance performance, usability, and cost.
• Translate business problems into mathematical frameworks and help enhance business adaptability for the solution.
• Validate AI system responses, including troubleshooting prompt engineering, agentic workflows and other aspects of a GenAI system.
• Develop processes and automation for accelerating validation of AI systems, while ensuring the proper degree of accuracy is maintained.

Skills / Qualifications

• 5+ years of professional experience in developing and deploying AI/ML solutions, with a strong emphasis on Generative AI technologies and applying these methods to physical systems and engineering workflows.
• Deep expertise in natural language processing (NLP), large language models (LLMs), and building agentic workflows for Generative AI with the ability to understand underlying mathematics and develop novel algorithms.
• Solid understanding of knowledge graphs, ontologies, and semantic technologies.
• Solid foundation and experiences in AI/ML on data processing, probability and statistics, EDA, feature engineering, modeling strategy, model development, and explainable AI.
• Proven track record of successfully developing and deploying multiple end-to-end Generative AI solutions, notably multi-agent systems, in business environments.
• Proficient in Python and widely used ML frameworks such as Tensor Flow, PyTorch, and Scikit-learn.
• Proficient in Generative AI frameworks such as Langchain, Prompt flow, or Copilot Studio
• Proven ability to uncover meaningful insights from complex datasets.
• Strong drive toward hands-on testing of hypotheses and rapid validation of assumptions through data.
• Strong communication, collaboration, and problem-solving skills.
• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Engineering, or a related field.

Preferred Knowledge/Skills

• Experience in the…