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# Analytics & AI Delivery Lead for Global Services & Commercial

- **Company:** GE Vernova
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Big Data, Cloud Computing, Program Optimization, Cyber Security, Data Governance, Digital Technology, Python (Programming Language), Machine Learning, Oracle (Applications), Power BI, SAP (Applications), Software Deployment, SQL Databases, Tableau (Software), Enterprise Data Management, Apache Spark, Data Strategy, Information Technology, Data Lineage, Data Analytics, Performance Monitor, Data Management, Databricks
- **Published:** September 4, 2026
- **Apply:** https://jobs.military.com/career/327850/ai-analytics-delivery-lead-florida-fl

## About the Role

* Bachelor's degree in Business, Computer Science, or a STEM-related field, including Science, Technology, Engineering, or Mathematics.\n
 * Minimum of ten years of experience in data management, business intelligence, data analytics, or a related discipline.\n
 * Minimum of eight years of technical experience, with demonstrated leadership across multiple functions and disciplines within a product or delivery organization.\n
 * Experience with Global Services & Commercial platforms and applications.\n
 * Demonstrated success leading at least two significant transformation initiatives, including organizational change management and the delivery of measurable business outcomes.\n, * Technical Proficiency: Demonstrated experience working in Agile and SAFe environments, with strong knowledge of enterprise data and analytics technologies such as Power BI, Tableau, SQL, SAP, Oracle, and Databricks. Familiarity with cloud, big data, and AI/ML technologies, including AWS, Python, Spark, and Java, is highly desirable.\n
 * Business and Domain Expertise: Strong understanding of Global Services & Commercial value streams and the integration of transactional and analytical data to enable actionable insights and measurable business value.\n
 * AI and Analytics Strategy: Solid knowledge of data governance, master data management, and the end-to-end AI and machine learning lifecycle, including data readiness, proof-of-concept execution, MVP development, production deployment, and ongoing optimization.\n
 * Strategic Leadership: Proven ability to lead transformation, navigate competing priorities, influence senior stakeholders, and translate complex technical concepts into clear, actionable insights for non-technical business leaders.\n
 * Cross-Functional Collaboration: Demonstrated ability to build inclusive, high-performing teams and collaborate effectively across Digital Technology, Global Services & Commercial and other functional organizations to align product strategy with operational priorities.\n
 * Governance and Risk Management: Strong commitment to enterprise standards and controls, including cybersecurity, SOX compliance, data governance, privacy, application controls, and regulatory requirements.\n
 * Process Improvement: Experience applying Lean principles, structured problem-solving, and continuous-improvement methodologies to simplify processes, establish standard work, and improve the scalability and performance of the product portfolio.\n
 * Influential Communication: Exceptional interpersonal and communication skills, with the ability to mentor and energize teams, establish a shared vision, build alignment, and maintain momentum through complex technical and organizational challenges.\n

## Description

* Cross-Functional Leadership: Serve as the primary liaison among executive stakeholders, Digital Technology, business operations, and delivery partners to align requirements, priorities, and execution with strategic business objectives.\n
 * Operational Excellence: Drive simplification, standardization, and delivery rigor by facilitating workshops and implementing improvements across tools, processes, and workflows.\n
 * Requirements and Backlog Management: Translate complex business needs into well-defined features, user stories, acceptance criteria, and prioritized product backlogs using agile or hybrid delivery methodologies.\n
 * Data, Risk, and Compliance Governance: Ensure that all analytics and AI solutions comply with enterprise standards for data quality, architecture, cybersecurity, internal controls, privacy, and regulatory requirements.\n
 * Standard Work and Platform Optimization: Establish robust standard work, simplify complex delivery processes, and continuously optimize analytical platforms and operating models for scalability, reliability, and performance.\n
 * Performance Monitoring and Value Realization: Define product KPIs, monitor adoption and user feedback, identify performance trends, and drive continuous product enhancements that deliver measurable business outcomes.\n
 * Automation and Productivity: Identify opportunities to automate manual activities, improve end-to-end process and data lineage, and partner with enterprise data organizations to increase delivery efficiency and overall team productivity.\n


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