Head of Data Strategy and Enablement

Posted 6 Days Ago
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New York, NY, USA
In-Office
160K-288K Annually
Expert/Leader
Fintech • HR Tech • Insurance • Consulting
The Role
Leads Marsh Re’s global data strategy and a multidisciplinary team of approximately 20 data engineers, scientists, developers, and product managers. Drives client-facing analytics advisory, scalable data and AI product development, enterprise data governance, cloud data architecture, machine learning, GenAI, MLOps, and responsible AI. Owns product lifecycle, commercialization, roadmap prioritization, executive reporting, team development, and collaboration with IT to industrialize innovation across the firm.
Summary Generated by Built In
Company:Marsh

Description:

Reporting to the Chief Operating Officer, this combined commercial, product, and technical leadership role drives the firm’s data strategy, enabling colleagues to benefit from our extensive data platform, and derive insights which deliver value to them and our clients.  Leading ~20 experts across the US, UK and Brazil, the team innovates with data technologies, including extensive use of AI capabilities, to continuously improve the data-driven capabilities of Marsh Re.


There is an additional focus on client advisory: the data-led reinsurance analytics work that wins and retains business. An emerging forward-deployed practice will support broking and analytics colleagues who are advising clients, using the data and AI products we’ve built on our data lake. You will turn those learnings into new data and AI products that scale across the client base and help push the frontier of Marsh Re’s data and AI work.


This role is based in New York City.


We will rely on you for:Client advisory
  • Support analytics-led advisory that wins new business and retains clients—bringing quantitative firepower to clients’ risk and capital decisions
  • Engage clients and markets with the firm’s internally built, AI-oriented products (built on our data lake), making them a reason that clients engage and stay
  • Advise clients on building their own data and AI strategy: assess where they are, design the target operating model and roadmap, and help them stand up scalable AI capabilities — with the credibility of a firm that has done it (proof-by-practice, not slideware)
  • Deploy engineers forward (embedded in our broking teams) to solve real problems using clients’ actual data
  • Co-develop and discover new, scalable AI products with our broking, analytics and advisory teams, shaping high-value use cases into repeatable solutions

  • Product innovation that scales a deliberate feedback loop: turn what forward-deployed teams learn in the field into productized data/AI capabilities that scale across the client base — build once, deliver to many
  • Own the data-product lifecycle (discovery → delivery → launch → continuous improvement); build revenue-generating products and scale them across clients and markets
  • Prioritize strictly by client value, commercial impact, and feasibility — avoid one-offs that don’t generalize


Frontier data, AI & innovation platform
  • Lead the firm’s frontier data and related AI work: net-new capability, applied AI/GenAI, and the data foundations that new models depend on — keeping the firm ahead of the market
  • Advance machine learning, predictive analytics, and applied GenAI products from research into production
  • Partner closely with GC IT to industrialize what the team provides — moving mature prototypes and IP cleanly from innovation into firm-wide production and scale
  • Champion data quality, governance, security, and responsible AI.

Data Strategy & Governance
  • Further extend our enterprise-wide Data Governance framework that includes:
    • Clear governance, ownership, and policies: defined data ownership, management and stewardship across the business and IT, a standardized metadata catalogue, and policies for access
    • Modern, scalable cloud-native architecture based on group strategic platforms, including Azure Data Lake (ADLS), Databricks, DBT and PowerBI
    • Trusted data through quality and master-data management: form-wide data quality rules, and automated profiling and remediation
  • Value delivery: analytics, MLOps, and a data-driven culture to deliver Client Advisory capabilities as described in the next section


People & organization
  • Leads with growth-oriented leadership mindset—coaching others, elevating performance through timely feedback, and building an inclusive environment that supports accountability and development.
  • Lead and mentor the team — data engineers, alongside data scientists, software developers, and product managers — managing technical leads and product managers
  • Build a culture that pairs engineering rigor with commercial and product instinct, and is comfortable engaging with internal and external clients
  • Lead the quarterly business reviews delivered to Executive Committee members as well as investment cases and roadmap trade-offs.


What you need to have:
  • 12–15+ years in data/analytics/AI, 2+ in senior leadership of a
    multidisciplinary team
  • Proven track record turning analytics into commercial outcomes —
    winning/retaining business or building products that do
  • Demonstrated ability to build and scale data/AI products (productization, not bespoke delivery)
  • Client-facing credibility — able to lead advisory engagements and engage with client and executive teams.
  • Strong command of data architecture and pipelining, ML algorithms, and applied AI — technical enough to lead the technical leads
  • Experience managing both engineering leads and product managers, and setting roadmap
  • A fast study — proven ability to master complex, unfamiliar domains quickly and operate credibly alongside subject-matter experts
  • Excellent executive communication and stakeholder management
  • Advanced degree in a quantitative field (or equivalent demonstrated experience)


What makes you stand out:
  • Experience in insurance, reinsurance, or financial services
  • Background at a major technology company, high-growth startup, or data/AI consultancy
  • Experience with a forward-deployed / embedded client-delivery model
  • Hands-on experience with LLM/GenAI in production, with responsible AI lens

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, veteran status (including protected veterans), or any other characteristic protected by applicable law. If you have a need that requires accommodation, please let us know by contacting [email protected].

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.

The applicable base salary range for this role is $160,200 to $288,400.

The base pay offered will be determined on factors such as experience, skills, training, location, certifications, education, and any applicable minimum wage requirements. Decisions will be determined on a case-by-case basis. In addition to the base salary, this position may be eligible for performance-based incentives.

We are excited to offer a competitive total rewards package which includes health and welfare benefits, tuition assistance, 401K savings and other retirement programs as well as employee assistance programs.

Skills Required

  • 12–15+ years of experience in data, analytics, or AI
  • At least 2 years of senior leadership experience managing a multidisciplinary team
  • Proven success turning analytics into commercial outcomes, including winning or retaining business or building revenue-generating products
  • Experience building and scaling data and AI products through productization rather than bespoke delivery
  • Client-facing credibility and ability to lead advisory engagements with clients and executive teams
  • Strong knowledge of data architecture, data pipelines, machine learning algorithms, and applied AI
  • Experience managing engineering leads and product managers and setting roadmaps
  • Ability to quickly master complex, unfamiliar domains and work credibly with subject-matter experts
  • Excellent executive communication and stakeholder management skills
  • Advanced degree in a quantitative field or equivalent demonstrated experience
  • Experience in insurance, reinsurance, or financial services
  • Background at a major technology company, high-growth startup, or data/AI consultancy
  • Experience with a forward-deployed or embedded client-delivery model
  • Production experience with LLMs or GenAI and a responsible AI perspective

Marsh McLennan Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Marsh McLennan and has not been reviewed or approved by Marsh McLennan.

  • Leave & Time Off Breadth — Leave offerings are described as generous, including sizable PTO, paid holidays, paid sick days, and additional time off such as paid volunteer time and “Summer days.” These time-off benefits are portrayed as a standout part of the overall rewards package.
  • Healthcare Strength — Healthcare coverage is characterized as comprehensive, spanning medical, dental, and vision options, with additional supports like disability and life insurance and access to mental health resources and an EAP. The breadth of plan options is positioned as a core strength of the benefits package.
  • Retirement Support — Retirement benefits are framed as solid, with 401(k) programs and employer matching frequently highlighted alongside other financial programs. Stock purchase options are also referenced as an additional wealth-building component of the total rewards mix.

Marsh McLennan Insights

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The Company
HQ: New York, NY
78,000 Employees
Year Founded: 1871

What We Do

Marsh McLennan (NYSE: MMC) brings together nearly 78,000 experts in risk, strategy, and people across Marsh, Guy Carpenter, Mercer, and Oliver Wyman, serving clients in over 130 countries. Marsh enables enterprise worldwide by helping clients manage risks, transforming uncertainty into opportunity. Guy Carpenter helps clients grow profitably with reinsurance broking expertise, advisory services, and advanced analytics. Mercer helps organizations advance the health, wealth, and careers of their most vital asset — their people. Oliver Wyman’s expertise in strategy, operations, risk, and organization transformation changes what is possible for our clients, their industries, and society. Together, we combine a unique range of capabilities to help our clients solve problems, seize opportunities, and build lasting success in increasingly complex operating environments.

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