CURRENT EMPLOYEES - Please apply using "Jobs Hub" in Workday. This career site is for external applicants only.

Job Responsibilities:

Include but are not limited to

• Partner with Drilling, Completions, Production Operations, Marketing, and related stakeholders to understand workflows, user needs, data requirements, controls, and operational challenges, and identify, evaluate, and prioritize AI and automation opportunities based on business value, technical feasibility, risk, data readiness, and strategic alignment.
• Own the business problem definition, product vision, target users and workflows, value hypothesis, roadmap, priorities, success measures, and expected business outcomes, partnering with business sponsors and the AI Value & Economics Lead to establish baseline performance and the approach for measuring realized outcomes before significant investment.
• Lead product discovery to validate the business problem, user needs, workflows, constraints, value hypothesis, and potential solution approaches before significant production investment, using rapid prototypes, workflow simulations, data exploration, user testing, vendor capability assessment, and other lightweight experiments to reduce uncertainty and test assumptions.
• Translate business needs into clear product requirements, user stories, success criteria, acceptance criteria, and AI quality expectations.
• Manage the product backlog and make product scope and priority decisions; lead business validation and user acceptance testing; and hold product acceptance decision rights against defined requirements, acceptance criteria, user needs, and expected business outcomes.
• Partner with technology, data, security, governance, legal, risk, and operational subject matter experts to deliver scalable solutions that meet responsible AI, confidentiality, data quality, and compliance requirements.
• Represent Drilling, Completions, Production Operations, and Marketing stakeholder needs; coordinate cross-functional dependencies with Geoscience, Reservoir Engineering, Finance, and other business functions; and support user readiness and adoption.
• Own post-launch product performance and continuous improvement by monitoring adoption, AI performance, business outcomes, realized value, user feedback, and relevant risk measures, and prioritize the changes needed to improve product outcomes.

Required Qualifications:

• Bachelor's degree in Petroleum Engineering, Mechanical Engineering, Chemical Engineering, Industrial Engineering, Data Science, Information Systems, or a related technical field
• 5+ years of experience supporting drilling, completions, production operations, marketing, or a closely related operational function within oil and gas
• Experience leading cross-functional technology, analytics, process improvement, or business transformation initiatives in an operational environment
• Experience translating operational workflows and business needs into clear requirements, priorities, and measurable outcomes
• Experience working with operational, engineering, production, field, commercial, or analytics data and systems, including technologies such as Spotfire, WellView, Ignition, Snowflake, XSPOC, Python, Power BI, and similar platforms
• Experience delivering or supporting AI, machine learning, automation, data, or analytics products from concept through adoption

Preferred Qualifications:

• Direct Product Owner experience managing product roadmaps, backlogs, user stories, and acceptance criteria in an Agile environment
• Experience using AI-enabled rapid product discovery techniques, including prototyping, user testing, workflow simulation, data exploration, or lightweight experimentation to test assumptions and reduce uncertainty before development.
• Knowledge of AI model evaluation, operational data practices, responsible AI governance, model risk controls, and data quality requirements
• Experience leading digital transformation or change adoption across Drilling, Completions, Production Operations, Marketing, or field operations teams
• Familiarity with drilling performance optimization, completions execution, production surveillance, artificial lift optimization, production forecasting, operational reporting, and field data management workflows