Power and Utilities-Product Management-Data and AI - Manager
Job description
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Manager – Power & Utilities, Product Management, Data & AI
Experience: 10–14 years, including 10+ years in Power & Utilities, Energy, or asset-intensive industries and 2+ years of people or delivery leadership experience.
Role Summary
We are seeking an experienced Manager to lead Industrial AI product management for the Power & Utilities sector. The role will shape AI-enabled solutions across grid operations, asset performance, outage management, maintenance, safety, and operational intelligence, delivering measurable improvements in reliability, cost, resilience, and decision-making.
Key Responsibilities
- Own product strategy, roadmap, prioritization, and delivery governance for Power & Utilities AI engagements across grid, asset, reliability, safety, and operations use cases.
- Lead and coach Senior Consultants and Consultants, ensuring delivery excellence, domain rigor, high-quality client outputs, and team development.
- Act as a trusted client-facing product leader for roadmap discussions, executive updates, steering committees, workshops, and decision forums.
- Translate utility business needs into product capabilities, user journeys, success metrics, data requirements, and adoption plans.
- Collaborate with data science, engineering, architecture, and delivery teams to shape predictive, prescriptive, and GenAI-enabled solutions.
- Build reusable frameworks, accelerators, playbooks, and product assets to support repeatable delivery and practice growth.
Required Skills & Experience
- 10–14 years of experience in Power & Utilities, Energy, asset-intensive industries, industrial technology, or consulting, with strong exposure to digital, analytics, or product-led delivery.
- Strong understanding of grid operations, asset management, reliability, maintenance, safety, field operations, and utility business processes.
- Demonstrated experience leading consulting, product, analytics, or technology delivery teams in a client-facing environment.
- Strong executive communication, stakeholder management, negotiation, facilitation, and advisory skills.
- Proven ability to own outcomes, timelines, risks, dependencies, quality, and commercial commitments across multiple workstreams.
- Define and prioritize AI, ML, and GenAI roadmaps linked to reliability, asset performance, maintenance, safety, and customer outcomes.
- Strong grasp of predictive and prescriptive analytics concepts, including failure prediction, escalation modelling, anomaly detection, risk scoring, and optimization.
- Evaluate data and platform decisions across SCADA, GIS, AMI, OMS, ADMS, EAM, IoT, cloud platforms, and utility data models.
- Frame business cases and ROI narratives for outage intelligence, asset performance, field copilots, predictive maintenance, and operational search.
- Working knowledge of industrial data governance, data quality, cybersecurity, privacy, access control, and regulatory considerations.
- Apply NLP, semantic search, embeddings, and retrieval-augmented generation for outage, engineering, customer, and maintenance data.
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