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Marsh is seeking candidates for our open Data and Innovation Leader. This is a remote position.
What can you expect:
The Data and Innovation Leader is a senior role that operates at the intersection of business strategy, initiative leadership, and technical delivery. This person shapes strategy with business sponsors, leads cross-functional project teams, and drives execution to measurable outcomes, without building permanent organizational stovepipes or owning products end-to-end.
Think of this as a consulting-style engagement model inside a large enterprise: leading high-priority initiatives, mobilizing resources (builders, engineers, data specialists, business experts), delivering value, and then moving on to the next critical challenge. The goal is not to create permanent product ownership silos, but to unblock, accelerate, and deliver on strategic priorities that matter to the business.
This role requires someone comfortable with ambiguity and fluidity, because both are features, not bugs. The specific domains, initiatives, and challenges will shift based on organizational priorities. Today it might be placement data strategy; tomorrow it could be claims transformation or reimagining our careers business. The constant is the ability to step in, lead, and drive results.
This role operates with a business co-sponsor. You are not a requirements-taker or delivery shop. You co-own strategy, co-create solutions, and share accountability with business leaders for outcomes. This is a true partnership model: two (or three) in the box, where both sides shape what gets built and both are accountable for results.
Shape strategy with the business: Partner with senior business and functional leaders to define what matters, why it matters, and how to deliver it. Bring data, process insights, and market context to the table. Challenge assumptions. Help prioritize and sequence initiatives.
Lead projects end-to-end: Drive execution from strategy through to value realization. Mobilize cross-functional teams (engineers, data architects, analysts, business stakeholders). Make tradeoffs. Unblock obstacles. Own delivery momentum and outcomes.
Engage directly with the work: Understand technical complexity. Participate in architecture discussions. Review data models. Engage with clients or end users when appropriate. Stay close enough to the work to lead with credibility.
Build and hand off: Lead initiatives that may require building products, tools, or capabilities, but with an explicit handoff plan. Once value is delivered and something needs long-term maintenance, transition it to technology/AMS teams. Then move to the next priority.
Operate across domains: Work flexibly across Marsh's businesses: placement, claims, policy management, health & benefits, careers, reinsurance, depending on where the biggest opportunities and under-baked initiatives are. Domain expertise in one area is valuable, but you won't be locked into it.
We will count on you to:
Co-Own Strategy with Business Sponsors: Partner with business leaders to shape initiative strategy, define value, and translate ambition into executable plans. Identify and prioritize opportunities using data, process insights, and business context. Bring rigor to opportunity sizing, success metrics, and value tracking & Challenge scope, sequence, and feasibility to ensure initiatives are ambitious but realistic
Lead Project Delivery: Drive cross-functional teams (engineers, data architects, analysts, business experts) to deliver outcomes, not just outputs. Orchestrate work across a matrixed organization with limited direct authority; lead through influence, clarity, and momentum. Make delivery tradeoffs (scope, time, quality) transparently and with business partners. Manage risks, dependencies, and stakeholder expectations; communicate progress and issues clearly.
Mobilize and Integrate Diverse Skill Sets: Understand what's needed to deliver (data engineering, analytics, software development, process change) and compose the right team. Work effectively with technical teams: understand architecture, data models, integration patterns, without being the one to build them. Engage with end users, clients, and business stakeholders to validate direction and drive adoption & connect business imperatives with technical feasibility; translate between both worlds
Drive Execution to Value Realization: Own outcomes, not just delivery milestones; ensure what gets built drives measurable impact. Establish metrics to track adoption, performance, and ROI; use data to course-correct. Build feedback loops with business sponsors and end users to iterate and improve & plan for handoff: ensure long-term run/maintenance transitions to the right teams when appropriate
Operate with Flexibility Across Domains: Move between initiatives and domains based on organizational priorities: placement one quarter, claims the next, careers after that. Build reusable patterns and frameworks (e.g., discovery templates, value models, governance rhythms) that scale across engagements & Bring a consulting mindset: swarm a problem, deliver value, transition ownership, move to the next challenge.
What you need to have:
A minimum of 8 years in roles involving product leadership, consulting, digital transformation, or technology strategy in complex, matrixed organizations.
What makes you stand out:
Demonstrated success leading ambiguous, cross-functional initiatives from strategy through delivery with measurable outcomes.
Strategic thinking and execution: Able to shape strategy and drive it through to outcomes. Balance vision with delivery discipline.
Consulting-style engagement leadership: Comfortable operating under ambiguity, building co-ownership with sponsors, leading through influence in matrixed environments.
Cross-functional team leadership: Proven ability to mobilize and lead diverse teams (business, technology, data, analytics) without direct authority.
Business and technical fluency: Can engage credibly in both business strategy discussions and technical architecture conversations. Understand what's possible, what's hard, and what matters.
Analytics and data fluency: Strong understanding of the value of analytics and what's possible with modern data, ML, and AI capabilities. Able to partner effectively with data and analytics teams to bring insights and solutions to life. Working knowledge of analytics approaches and tooling (e.g., data platforms, BI, predictive models, ML lifecycle concepts) sufficient to guide direction, challenge assumptions, and make informed tradeoffs. You don't need to build the models or write the code, but you need to understand the art of the possible and help translate business problems into analytical solutions.
Product management mindset: Strong instincts for discovery, prioritization, backlog management, and adoption, even if you're not permanently "owning" a product.
Domain expertise: Prior experience in insurance brokerage, benefits consulting, or adjacent platforms. Specifically in areas like placement workflows, claims operations, policy/binder management, or use of exposure and loss data. Domain knowledge in one area is valuable; you won't be confined to it.
Technical prototyping skills: Familiarity with modern AI-assisted development tools, ability to rapidly prototype concepts to accelerate stakeholder feedback and iteration.
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