US Health & Benefits Data Strategist

Company:

Description:

The US H&B Data Strategist is responsible for defining and advancing the US Health & Benefits (H&B) business data strategy across digital products, platforms, and consulting solutions. This role leads the development of the US H&B data vision, strategy, and cross-functional roadmaps to ensure data assets are intentionally structured, governed, and leveraged to enable innovation and support scalable digital capabilities. Serving as a strategic partner to product, platform, analytics, and consulting leaders, the Data Strategist connects business objectives to practical data investment decisions, ensuring data is treated as a core product capability and a durable enterprise asset that drives differentiated client value.

Key Responsibilities

Data Strategy & Vision

• Define and evolve the US H&B data strategy in alignment with product, platform, analytics, and innovation priorities, ensuring clear outcomes, sequencing, and value realization.

• Establish a strategic point of view on how US H&B should use data to differentiate offerings (e.g., insight-driven consulting, benchmarking, predictive analytics, workflow automation) and create competitive advantage.

• Translate business needs into an actionable multi-horizon roadmap of data capabilities (foundational, enabling, and differentiating) with measurable success metrics.

Data Product Identification & Development

• Identify opportunities to transform raw and fragmented data into structured, reusable, well-documented data products that are discoverable and fit-for-purpose across multiple use cases.

• Drive standardization of metric definitions and calculation logic across US H&B to enable consistent reporting, benchmarking, and analytics at scale.

• Define how data should be modeled, curated, and reused across products and solutions (e.g., canonical entities, shared measures, reference data, metadata standards).

Product & Platform Partnership

• Ensure data models, pipelines, and governance approaches align with the long-term product and platform strategy, enabling modularity, reuse, and scale.

• Partner with Product, Engineering, and Analytics to embed strong data foundations into solution design (e.g., instrumentation, lineage, quality controls, semantic layers).

• Support the development of benchmarking, analytics, and insight capabilities by defining required data inputs, readiness criteria, and operationalization patterns.

Data Governance & Alignment

• Partner with Marsh Innovation and Data Office and enterprise data teams to align US H&B efforts to enterprise data standards, policies, and shared capabilities.

• Advocate for clear data ownership, stewardship, access principles, and usage policies; help establish processes to ensure adoption and sustained compliance across US H&B.

• Proactively identify and mitigate data duplication and fragmentation across tools, teams, and products by promoting common assets, shared definitions, and intentional reuse.

Insights & Value Generation

• Identify opportunities to create new insights, improve analytics, and increase client value by aligning data strategy with business priorities and user workflows.

• Partner with business and product leaders to define new metrics and analytical frameworks, including how insights are packaged into products and consulting offerings.

• Define value hypotheses and measurement approaches for data initiatives (e.g., revenue impact, margin improvement, adoption, cycle time reduction, quality/accuracy gains).

Innovation & Market Opportunity Support

• Partner with the Health Innovation Studio to evaluate data-driven opportunities and define data requirements for potential products, accelerators, and analytics solutions.

• Assess feasibility and value of new datasets and data sources (internal and external), including partnership and acquisition considerations where relevant.

• Represent data strategy perspectives in cross-functional forums to support prioritization, decision-making, and investment planning.

Additional Skills & Experiences

• Data Product Mindset: Treats data as a product with defined users, quality expectations, documentation, governance, and lifecycle management.

• Analytical Rigor: Brings structured problem-solving, metric discipline, and hypothesis-driven approaches to roadmap and investment decisions.

• Communication & Stakeholder Management: Builds trust with technical and non-technical leader