[Hiring] VP OmniAnalyst Product Manager @Sedgwick

Role Description

The VP OmniAnalyst Product Manager– AI Enabled Enterprise Data Products is responsible for defining and executing the product strategy, roadmap, and business outcomes for Sedgwick’s enterprise AI-enabled data product portfolio. This role owns a portfolio of strategic data products including:

• Enterprise AI Analyst and conversational analytics platforms that allow users to ask natural language questions and receive trusted insights, visualizations, recommendations, and analysis.
• Enterprise data sharing, data exchange, marketplace, semantic layer, data catalog, and self-service analytics capabilities.
• AI-enabled operational decision support products and analytical applications.

The VP serves as the bridge between business strategy, data strategy, AI innovation, technology execution, governance, and client value realization. This role leads Product Managers and Product Owners while partnering with Data Engineering, Architecture, Security, Governance, AI Engineering, Analytics, and Business leaders to deliver secure, scalable, governed, and measurable 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.

Requirements

• Expert knowledge of Agile methodologies, product operating models, portfolio management, prioritization, roadmap development, and outcome measurement.
• Ability to translate business and portfolio strategy into product vision, execution standards, and measurable value.
• Deep understanding of Data as a Product principles, modern data platforms, data mesh, data fabric, governance, semantic modeling, metadata, lineage, and enterprise analytics architectures.
• Strong understanding of AI, generative AI, conversational analytics, augmented decision-support platforms, and responsible AI practices.
• Experience with enterprise data sharing, security, privacy, governance, compliance frameworks, and risk management.
• Strong executive communication, stakeholder management, product adoption, organizational change, and people leadership capabilities.
• Ability to balance business value, technical complexity, investment, risk, and operational impact.

Benefits

• Work-life balance.
• Growth opportunities.
• Caring culture.