✦ Luna Orbit — AI & Machine Learning

IT Manager, Data Science & AI

at Marathon Oil

📍 6 Locations Unknown 💰 $137K – $206K USD / year Posted April 14, 2026
Salary $137K – $206K USD / year
Type Not Specified
Experience senior
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

Marathon Oil seeks an IT Manager of Data Science & AI to lead and scale a team delivering advanced machine learning, deep learning, and generative/agentic AI solutions. The role owns end-to-end AI/ML lifecycle delivery and ensures enterprise standards for security, governance, ethics, and responsible AI while leading people and projects.

  • Manage daily team operations and people leadership (recruitment, retention, performance)
  • Define and execute AI and data science roadmap aligned to enterprise priorities
  • Oversee design, training, validation, and operationalization of machine learning, deep learning, and generative/agentic AI models
  • Ensure AI solutions meet security, governance, ethics, and responsible AI standards
  • Plan and lead AI/data science IT projects within time, budget, and quality targets

The technical scope centers on operationalizing AI/ML initiatives, including model design, training, validation, deployment, and ongoing operational support. The manager must enforce data governance, ethics, and responsible AI frameworks while standardizing workflows and reusable code libraries for enterprise scalability.

The ideal candidate is a senior IT/data science leader who can manage AI/ML initiatives end-to-end, from strategy and model design through training, validation, deployment, and operational support. They bring strong people leadership experience and ensure enterprise-grade security, governance, ethics, and responsible AI practices while scaling advanced machine learning, deep learning, and generative/agentic AI solutions.

Lead delivery of advanced machine learningdeep learning and generative AI solutionsincluding emerging agentic AI capabilitiesAccountable for managing the full lifecycle of AI/ML initiatives-from strategy development to model designtrainingvalidationdeploymentand operational supportEnsure solutions adhere to enterprise standards for securitygovernanceethicsand responsible AIRecruitmentdevelopmentretentionand performance management
Develop internal best practicesreusable code librariesand standardized workflows for AI/ML projects
AI and advanced analytics strategymachine learningdeep learninggenerative AIagentic AIAI/ML lifecycle managementmodel designmodel trainingmodel validationmodel deploymentoperational supportdata governanceethicsresponsible AIsecurity governancereusable code librariesstandardized workflowspeople leadershiprecruitmentperformance management
AI and advanced analytics strategymachine learningdeep learninggenerative AIagentic AI capabilitiesAI/ML lifecycle managementstrategy developmentmodel designmodel trainingmodel validationmodel deploymentoperational supportdata governanceAI governanceethics frameworksresponsible AIsecurity standards adherencereusable code librariesstandardized workflows for AI/ML projectsteam operations managementrecruitmentdevelopmentretentionperformance managementIT project planningIT project leadershiptechnology systems availabilitytechnology systems reliabilitytechnology systems securitylow- to medium-complexity IT projectsbudget managementtimeline management
People leadershipMentorshipCulture of innovationContinuous improvementStakeholder managementCollaborationInfluencing stakeholdersCross-functional communicationInnovation mindset
Industry Energy
Job Function Lead enterprise data science and AI delivery through people leadership, AI/ML lifecycle ownership, and responsible governance.
Role Subtype ML Engineer
Tech Domains AI & Machine Learning
IT ManagerData Science & AImachine learningdeep learninggenerative AIagentic AIartificial intelligenceAI and advanced analyticsenterprise AI strategyadvanced analytics strategyAI/ML lifecyclemodel designmodel trainingmodel validationmodel deploymentoperational supportdata governanceethicsresponsible AIsecurity governancereusable code librariesstandardized workflowspeople leaderrecruitmentperformance managementoperationalizationpeople leadership

Must have experience managing the full lifecycle of AI/ML initiatives (strategy through deployment and operational support), Must ensure adherence to enterprise standards for security, governance, ethics, and responsible AI, Must have people leadership experience (recruitment, performance management)

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