Job Description Summary

The Data & AI Delivery Lead for Commercial & Parts is responsible for defining, owning, and executing the end-to-end data, analytics, and AI product strategy for Gas Power’s Commercial organization—including Sales, Marketing, and Pricing—and Parts Fulfillment. This leadership role ensures that analytical and AI products are delivered on time, within budget, and to high quality standards while generating measurable business value.

Serving as a strategic bridge across executive business stakeholders, Digital Technology, analytics operations, Services, and ERP teams, the leader will establish the product vision, define complex business and technical requirements, and translate business priorities into scalable, user-centric data and AI solutions. The role will orchestrate cross-functional delivery, drive adoption and integration into day-to-day operations, and continuously improve product performance across the Commercial and Parts domains.

As the AI Delivery Leader, this individual will oversee the full AI product lifecycle—from data readiness assessments and Proof-of-Concept execution through MVP delivery, production deployment, and operational transition. By combining deep business-process understanding with strategic roadmap ownership and disciplined delivery oversight, the leader will ensure that data and AI investments remain aligned with operational priorities, customer needs, and evolving market opportunities.

Job Description

Roles and Responsibilities

In this role, you will:

• AI Data Readiness and Delivery: Partner with the AI Strategy Data Science and AI Architecture teams to lead data-readiness activities, technical execution of proofs of concept, MVP development, and the scaling of validated solutions into high-impact, production-grade AI products.
• AI Strategy and Demand Management: Partner with the AI Strategy Portfolio team to build and maintain a strong demand pipeline, establish effective intake and prioritization processes, and enable a stable, scalable AI delivery model.
• Data and Analytics Strategy and Lifecycle Ownership: Partner with Data Architects to define and execute the end-to-end roadmap for Commercial and Parts data, analytics, and AI products—from ideation and proof of concept through MVP delivery, production deployment, and ongoing product optimization.
• Partner and Capacity Management: Translate demand and priorities from the agile planning process into actionable capacity plans. Lead the Program Increment planning process and work with OCIO and strategic partners to onboard the right resources and capabilities for both analytics and AI delivery.
• Cross-Functional Leadership: Serve as the primary liaison among executive stakeholders, Digital Technology, business operations, Services, ERP teams, and delivery partners to align requirements, priorities, and execution with strategic business objectives.
• Operational Excellence: Drive simplification, standardization, and delivery rigor by facilitating workshops and implementing improvements across Commercial and Parts analytical tools, processes, and workflows.
• 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.
• 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.
• 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.
• 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.
• 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.

Qualification

• Bachelor’s degree in Business, Computer Science, or a STEM-related field, including Science, Technology, Engineering, or Mathematics.
• 11+ years of experience in data management, business intelligence, data analytics, or a related discipline.
• Experience with Salesforce platforms and enterprise resource planning systems is preferred.
• Demonstrated success leading at least two significant transformation initiatives, including organizational change management and the delivery of measurable business outcomes.

Desired Characteristics

• 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.
• Business and Domain Expertise: Strong understanding of Commercial and Parts value streams, ERP and Salesforce ecosystems, and the integration of transactional and analytical data to enable actionable insights and measurable business value.
• 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.
• 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.
• Cross-Functional Collaboration: Demonstrated ability to build inclusive, high-performing teams and collaborate effectively across Digital Technology, Services, Sales, Marketing, Finance, ERP, and other functional organizations to align product strategy with operational priorities.
• Governance and Risk Management: Strong commitment to enterprise standards and controls, including cybersecurity, SOX compliance, data governance, privacy, application controls, and regulatory requirements.
• 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.
• 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.

Additional Information