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Decision Intelligence Director
Marathon Petroleum Corporation. Lead Marathon’s enterprise Decision Intelligence capability across Business Intelligence, Machine Learning, Generative AI, AI agents, and agentic systems .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading enterprise Decision Intelligence initiatives, including Business Intelligence, Machine Learning, and Generative AI, while establishing robust frameworks and governance for AI capabilities. Proven ability to manage diverse teams, drive strategic vision, and implement effective analytics solutions in complex environments.
Highest-signal resume keywords
Enterprise Decision Intelligence StrategyMachine Learning LeadershipGenerative AI ArchitectureAnalytics GovernanceTeam Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Business IntelligenceMachine LearningGenerative AIAI AgentsPredictive ModelingMLOpsData AnalyticsEnterprise AI FrameworksLifecycle ManagementPerformance Measurement
Soft Skills
LeadershipCoachingCollaborationStakeholder InfluencePerformance Management
Tools & Technologies
Microsoft FoundryAzure ServicesDatabricksIndustrial AI PlatformsAgentOps Practices
Industry Keywords
Complex Regulated EnvironmentsAsset-Intensive IndustriesEnergy SectorManufacturingData Quality
Tech Stack
Tools & technologiesAzureCyber Security
About the role
Key responsibilities & impact- Lead Marathon’s enterprise Decision Intelligence capability across Business Intelligence, Machine Learning, Generative AI, AI agents, and agentic systems
- Set the strategy and operating model connecting trusted data, analytics, enterprise knowledge, and AI to improve business decisions
- Provide leadership for BI and Machine Learning through their managers and own the vision, framework, platform strategy, and implementation model for enterprise AI
- Lead managers and individual contributors through coaching, recruitment, development, retention, performance management, and succession planning
- Collaborate with stakeholders and senior management on technology risks, opportunities, prioritization, and cost-effective solutions
- Oversee planning, design, implementation, and measurement of IT systems
- Define and execute the enterprise Decision Intelligence strategy and roadmap
- Provide executive leadership for enterprise reporting, dashboards, self-service analytics, semantic models, KPI definitions, adoption, and governance
- Provide executive leadership for advanced analytics, predictive and optimization models, computer vision, model lifecycle management, MLOps, production monitoring, and value realization
- Establish enterprise AI frameworks, platform strategies, reference architectures, reusable services, engineering patterns, evaluation standards, AgentOps practices, and operating models
- Establish strategy for enterprise agents and agentic AI, including identity, approved tools, orchestration, human approval, evaluation, observability, lifecycle management, and safe controls
- Advance the Enterprise Knowledge System by connecting governed data products, semantic models, metadata, business context, ontologies, knowledge graphs, documents, skills, tools, and prior decisions
- Create federated delivery models and clarify decision rights, escalation routes, support expectations, and product accountability
- Lead AI capabilities from exploration through pilot, production, and scale with business ownership, success measures, readiness, support, adoption, and benefits realization
- Partner with architecture, engineering, governance, cybersecurity, legal, risk, platform, and business teams to embed controls
- Assess emerging analytics and AI technologies and recommend their fit within Marathon’s target architecture
- Establish portfolio and performance measures for outcomes, adoption, quality, reliability, cost, model and agent performance, risk, reuse, and operational health
- Influence senior stakeholders to prioritize opportunities and align investment, architecture, and delivery capacity
Requirements
What you’ll need- Bachelor's degree in Computer Science, Information Technology, Management Information Systems, Engineering, Business, or other computer-related degree required
- Twelve (12) or more years of diversified IT experience required
- Five (5) or more years directly managing professional staff required
- Experience leading multiple analytics or AI disciplines through managers and senior technical leaders strongly preferred
- Demonstrated experience establishing or materially transforming an enterprise analytics, machine learning, or AI capability from strategy through governed production adoption required
- Experience defining enterprise AI architecture, platform capabilities, operating models, governance, and lifecycle controls for agents or Generative AI strongly preferred
- Experience in a complex, regulated, asset-intensive, energy, manufacturing, or industrial enterprise preferred
- Knowledge or experience with Microsoft Foundry and Azure services, Databricks, application-native agents, industrial AI platforms, and relevant open standards
- Ability to establish security, privacy, responsible AI, data quality, resilience, and compliance controls
- Ability to define enterprise AI frameworks, platform strategies, reference architectures, reusable services, engineering patterns, evaluation standards, AgentOps practices, and operating models
Benefits
Comp & perks- Health insurance
- Vision insurance
- Dental insurance
- Paid time off
- 401k matching program
- Paid parental leave
- Educational reimbursement
- Discretionary company-sponsored annual bonus program