Job Description Summary

The Data & AI Delivery Leader for GE Vernova Power will unify data analytics and AI program leadership, lead overall Power analytics portfolio & strategy, AI transformational use case delivery, enable data consumption for AI, and enable citizen developer data consumption with AI. This role will oversee and transform the approach of traditional data & analytics across the Power, defining a cohesive strategy for analytics delivery, AI delivery, and AI data solutions that enables scalable, stable, and high-impact solutions. This role is central to advancing GE Vernova Power’s committed transformation to an AI-enabled enterprise

Job Description

Roles and Responsibilities

In this role, you will:

Strategic Vision & Roadmap

• Define and enable the Power Analytics and Data Strategy in close partnership with the Power Data Science & AI and HQ Analytics teams, ensuring tight alignment with business priorities and the broader GE Vernova AI vision
• Product Execution & Delivery:   Oversee AI Project Owners responsible for managing end-to-end product lifecycle, from ideation, deployment, to scaling.  Ensure successful deliver of AI solutions through vendor partners, AI Foundry, and internal stakeholders.  Drive agile product management practices tailored to AI/ML development
• Cross-Functional Leadership:  Collaborate closely with AI Architecture teams on scaleable, enterprise-grade solution design, model development, AI readiness, and IT business leaders on integration and adoption.  Act as the primary delivery bridge between AI strategy team and technical execution/delivery.
• Vendor & Partner Management:  Lead engagement with external vendors and delivery partners.  Ensure accountability for delivery quality, timelines, and outcomes.
• Prioritize and optimize the analytics product portfolio across domains and business processes to drive strategic coherence, eliminate redundancy, and maximize business impact
• Translate business needs into actionable use-case roadmaps, balancing short-term value delivery with long-term foundational investments that strengthen analytics maturity and business self service leveraging AI tools and capability
• Transition from a purely “deliverables” model to a product-centric mindset, emphasizing continuous iteration, feedback loops, and business ownership.
• Define metrics, SLAs, and KPIs for adoption, performance, and health of analytics products.
• Support business stakeholders through the AI initiation process and collaborate with the Power Data Science & AI team once concepts are approved for Proof-of-Concept (POC). This includes driving AI readiness activities and supporting all data related requirements.

AI Enablement & Data Readiness

• Partner closely with the Power Data Science & AI team to operationalize the AI Data Readiness Framework, ensuring data quality, accessibility, Interpretability, and reliability.
• Diversify and modernize visualization solutions, driving the transformation toward AI-enabled analytics tools that enhance insight generation and maximize business productivity

Product Stability, Governance & Cost Optimization

• Be accountable for overall analytics product reliability, performance, usage, and cost, ensuring all solutions remain stable, secure, and aligned with evolving business priorities.
• Establish a standardized governance model to oversee the analytics product landscape, conduct regular portfolio and cost reviews, and implement an operating model that drives transparency, alignment, and sustainable cost management across the Gas Power DnA ecosystem.
• Deliver end-to-end analytics product lifecycle management — from demand intake and prioritization to new development, optimization of existing products, and responsible retirement of legacy solutions.
• Define and track key metrics, SLAs, and KPIs across both program delivery and AMS support to ensure consistent quality, continuous improvement, and reliable analytics operations.

Business Partnership & Stakeholder Management

• Serve as the trusted Analytics to the Power business teams, driving data democratization and continuous data quality improvement—collaborating to shape strategy, validate investments, and translate analytics capabilities into measurable business outcomes.
• Lead the strategic partner engagement model, ensuring delivery excellence, capability development, and strong alignment with GE Vernova’s business priorities and technology vision.
• Foster proactive and transparent communication across HQ D&A Platform, Gas Power Analytics, and business stakeholders—providing clear visibility into