Remote VP, AI-Driven Enterprise Data Products

Sedgwick; Houston (TX); Remote; USD 180,000 - 240,000; Full time

Job summary

Sedgwick is seeking a VP OmniAnalyst Product Manager – AI Enabled Enterprise Data Products to define and execute the product strategy and roadmaps for Sedgwick’s enterprise AI-enabled data product portfolio.

You will lead Product Managers and Product Owners, partnering with Data Engineering, Architecture, Security, Governance, AI Engineering, Analytics, and business leaders to deliver secure, scalable enterprise capabilities.

Qualifications

• Bachelor’s degree in Business, Computer Science, Information Systems, Engineering, Data Science or related field required.
• Master’s degree preferred.
• 10+ years of progressive experience in Product Management, Data Products, Analytics Platforms, AI Products or Enterprise Technology.
• 5+ years leading Product Managers or Product Owners and managing product portfolios.
• Experience owning enterprise-scale data, analytics, AI, platform, reporting, self-service analytics, semantic modeling, AI/ML or conversational AI products.
• Experience defining product strategy, roadmaps, business cases, and measurable outcomes for data-driven products.
• Experience working in Agile or scaled Agile environments and leading cross-functional teams across Architecture, Data Engineering, Analytics, Security, Governance and Business stakeholders.

Responsibilities

• Define and own the multi-year vision, strategy, roadmap, business model, and investment priorities for enterprise AI and data products.
• Establish a product portfolio enabling business users, clients, and operational teams to discover, access, share, and analyze trusted enterprise data.
• Drive AI-powered analytical experiences that allow users to interact with enterprise data through natural language and conversational interfaces.
• Partner with executive leadership to identify opportunities that improve decision-making, efficiency, client experience, revenue growth, and cost optimization.
• Develop business cases, success measures, portfolio-level OKRs, and executive communications on progress, risks, and architectural implications.
• Oversee delivery across multiple teams, ensuring alignment between product strategy, technical execution, architectural direction, and client outcomes.
• Set expectations for backlog quality, acceptance criteria, prioritization, capacity planning, dependency management, and delivery risk mitigation.
• Own product portfolio KPIs and contributions to Product Group and enterprise OKRs, including quality, efficiency, sustainability, and value delivery.
• Ensure solutions comply with enterprise security, privacy, regulatory, governance and responsible AI requirements.
• Serve as the senior escalation point for product-related dependencies, risks, and prioritization conflicts.
• Establish product management practices for enterprise data products, including data-as-a-product principles.
• Define and manage reusable, governed data products supporting claims, finance, compliance, operations, client, and executive reporting needs.
• Drive adoption of semantic models, business glossaries, metadata, cataloging and self-service analytics capabilities.
• Lead product strategy for enterprise data-sharing solutions for internal consumers, clients, partners, and third-party integrations.
• Ensure data products are reliable, scalable, discoverable, secure, usable and supported by lineage and governance.
• Own the product vision for AI-powered analytics that provide trusted answers, insights, metrics, visualizations and recommendations through natural language interactions.
• Partner with business teams to identify high-value analytical use cases and decision-support opportunities.
• Define requirements for semantic layers, knowledge models, retrieval experiences, governance controls, trust mechanisms and user experiences.
• Measure AI product effectiveness through adoption, accuracy, user satisfaction, business impact and operational efficiency.
• Ensure AI-generated insights are explainable, governed, auditable and aligned with enterprise policies.
• Define strategy and roadmap for enterprise-scale data exchange and sharing capabilities.
• Partner with Security, Governance, Privacy and Legal teams to establish secure and compliant data-sharing frameworks.
• Drive capabilities for role-based access, entitlements, auditing, lineage, masking, client access controls and data-sharing agreements.
• Enable governed data product distribution across business units, clients, partners and external ecosystems while supporting growth, performance, compliance and resilience.
• Build strong relationships with business leaders, claims operations, finance, client services, technology leaders and external stakeholders.
• Translate business objectives and operational challenges into actionable AI and data product strategies.
• Communicate roadmap progress, risks, dependencies, investment needs and outcomes to executive leadership.
• Establish and monitor portfolio-level KPIs, OKRs and value realization metrics that trace strategy through implementation to business impact.
• Lead and develop Product Owners, Scrum Masters, and product delivery teams.
• Establish product management best practices across AI, data, analytics, and platform teams.
• Coach teams on customer-centric product development, Agile practices, outcome-based planning and value measurement.
• Foster a culture of innovation, experimentation, accountability, continuous learning and collaboration.

Skills

Agile methodologies

Portfolio management

Cross-functional leadership

Executive communication

Stakeholder management

Education

Bachelor’s degree in Business/CS/IS/Engineering/Data Science

Master’s degree preferred

Job description

Sedgwick is seeking a VP OmniAnalyst Product Manager – AI Enabled Enterprise Data Products to define and execute the product strategy and roadmaps for Sedgwick’s enterprise AI-enabled data product portfolio.

You will lead Product Managers and Product Owners, partnering with Data Engineering, Architecture, Security, Governance, AI Engineering, Analytics, and business leaders to deliver secure, scalable enterprise capabilities.