AI Strategy - Oil & Gas - Manager - Consulting

AI Strategy - Oil & Gas Sector - Manager (Consulting)

Location:

Anywhere in Country

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help build a better working world.

As part of our growing AI & Data practice, we are seeking a highly experienced Senior Manager to lead enterprise AI strategy and quantitative modeling efforts for our clients in the Oil & Gas sector. This individual will bring deep industry expertise and a proven track record of designing and operationalizing responsible, scalable, value‑aligned AI solutions. You’ll lead high‑impact client engagements focused on Generative AI, Agentic AI, MLOps and AI governance frameworks—driving measurable outcomes in upstream, midstream and downstream operations.

• Manage engagement delivery, ensuring quality and risk management throughout the project lifecycle.
• Manage client relationships, focusing on revenue generation and the identification of new opportunities.
• Manage resource plans and budgets for engagements, ensuring alignment with performance objectives.
• Define and implement enterprise‑wide AI and quantitative modeling strategy tailored to oil & gas value chains (e.g., asset optimization, drilling, trading, predictive maintenance).
• Establish AI governance frameworks that ensure responsible AI adoption, ethical use of data, model risk management and alignment with evolving regulations.
• Design and operationalize Agentic AI solutions to automate reasoning, planning and decision‑making tasks in complex environments.
• Drive the prioritization of AI use cases based on business value, feasibility and risk, ensuring ROI on AI initiatives.
• Lead multidisciplinary teams of data scientists, engineers and consultants to deliver end‑to‑end AI platforms and solutions.
• Partner with senior business and IT leaders to identify strategic opportunities and shape AI‑enabled business transformation.
• Implement and scale Model Ops and MLOps practices, ensuring transparency, reproducibility and monitoring of models in production.
• Lead AI solution architecture, including hybrid deployments on cloud (e.g., Microsoft Azure, Amazon AWS).
• Serve as a thought leader in emerging AI technologies, including Generative AI, foundation models, RAG and Agentic AI.
• Drive internal capability building and innovation in Responsible AI, agentic workflows and energy sector‑specific solutions.

To excel in this role, you will need a blend of technical and interpersonal skills. Your ability to navigate complex challenges and deliver innovative solutions will be crucial.

• Strong analytical and decision‑making skills to develop solutions to complex problems.
• Proven experience in managing client relationships and leading teams.
• Ability to communicate effectively and influence stakeholders at all levels.

• Bachelor’s degree required;
  Master’s degree preferred with focus in Computer Science, Applied Math or related field and prior consulting experience required.
• 5+ years of experience in technology consulting, digital transformation or AI‑driven business solutions.
• 3+ years of leading AI/ML projects, including team management and executive stakeholder engagement.
• Strong expertise in AI platforms and tools.
• Proficiency in data architecture design and modeling.
• Experience in digital transformation and IT effectiveness assessment.
• Knowledge of emerging technologies and technology strategy, vision and roadmap.
• Ability to build and manage relationships effectively.
• Strong exposure to oil & gas industry operations, value levers and use case landscape.
• Proven success in developing AI strategy and governance models, including frameworks for responsible AI, risk and compliance.
• Hands‑on experience with Generative AI frameworks (e.g., OpenAI, Hugging Face, Lang Chain, RAG).
• Experience architecting and scaling MLOps platforms and data science workflows in cloud‑native environments.
• Proficiency in Python and tools such as Pandas, PyTorch, Scikit‑learn, Spark and SQL.
• Experience with CI/CD, containerization…