Marsh Risk
Data Strategy Lead, Digital Client Experience (DCX) - Marsh

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Data Strategy Lead, Digital Client Experience (DCX) | Marsh | Hybrid | London
We are seeking a talented individual to join the Digital Client Experience (DCX) team at Marsh. This role will be based in London and is a hybrid position, with a requirement to work in the office at least three days per week.
DCX (Digital Client Experience) is a Marsh Risk unit that incubates and scales client-facing digital solutions, bringing together product, design, technology, analytics, and applied AI to help clients shape risk strategy, optimize risk transfer, and proactively manage and mitigate risk. This is a hands-on, strategic role at the intersection of data strategy, product management, knowledge architecture, AI enablement, governance, and business transformation. You will help shape how Marsh Risk transforms proprietary data, documents, analytics, and institutional expertise into reusable, well-governed, AI-ready knowledge assets. Working closely with colleagues across product, analytics, engineering, operations, and governance, you will help build the foundations for knowledge products that support client-facing solutions and more informed operational decision-making.
We will count on you to:
- Define the DCX data and knowledge strategy, setting a clear roadmap for converting proprietary information into reusable knowledge and data products.
- Prioritize high-value domains and use cases with business, content, product, and operations partners, ensuring focus on outcomes that matter.
- Build reusable knowledge products across areas such as client intelligence, claims intelligence, exposure data, risk engineering insight, benchmarking, policy wording, market appetite, and industry risk profiles.
- Bridge analytics and operations by embedding insight into workflows, processes, and day-to-day decision-making rather than limiting it to dashboards and reports.
- Define the knowledge layer, including core business entities, relationships, taxonomies, ontologies, semantic standards, and entity resolution across key business concepts.
- Establish governance, trust, evaluation standards, and operating models that support AI-ready knowledge products at scale.
- Support the use of AI and automation to accelerate discovery, classification, metadata extraction, data profiling, duplicate detection, and corpus preparation.
- Work with cross-functional teams to create feedback loops that continuously improve metadata, retrieval, quality, and usability of knowledge assets.
- Help define requirements for the AI-readiness of documents such as reports, presentations, contracts, broker notes, risk assessments, policy wording, claims summaries, and client deliverables.
- Partner with engineering teams to help shape tools that can search, retrieve, query, summarize, compare, and evaluate knowledge assets.
- Contribute directly to priority workstreams across DCX, ensuring ideas are translated into practical, usable solutions.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What you need to have:
- Proven experience in data strategy, data product management, enterprise data platforms, knowledge management, AI enablement, or digital product leadership.
- Demonstrated ability to bridge analytics and operations, translating data insight into operational practice and vice versa.
- Strong understanding of how AI systems use data, including retrieval-augmented generation, vector search, metadata, semantic layers, knowledge graphs, and agentic workflows.
- Experience working with complex enterprise data environments, including fragmented systems, inconsistent data quality, and mixed structured and unstructured sources.
- Demonstrated ability to partner with senior business leaders, technology teams, data governance, legal, compliance, and product teams.
- Experience defining data ownership, stewardship models, business glossaries, data quality frameworks, or domain data products.
- Strong product mindset, with the ability to connect technical enablement to business value and user adoption.
- Ability to operate in ambiguity and create structure across complex, cross-functional environments.
- Experience in financial services, insurance, risk advisory, professional services, or another data-rich regulated industry.
- Familiarity with modern lakehouse, data catalogue, data governance, and AI platform architectures.
- Familiarity with Databricks or comparable unified data and AI platforms, including Spark-based lakehouse environments.
- Experience preparing proprietary document corpora for AI search, summarization, and reasoning.
What makes you stand out:
- Exposure to ontology design, knowledge graphs, semantic modeling, or entity resolution.
- Working knowledge of enterprise AI governance, model evaluation, responsible AI, or AI risk controls.
- Hands-on experience building or scaling data products for client-facing or colleague-facing digital platforms.
- Enabled teams to adopt new data, knowledge, or AI capabilities in sustainable ways.


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Why join our team:
- We help you be your best through professional development opportunities, interesting work and supportive leaders.
- We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
- Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.
Marsh Risk is a business of Marsh (NYSE: MRSH), 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 about Marsh Risk, 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, civil partnership status, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. We are an equal opportunities employer. We are committed to providing reasonable adjustments in accordance with applicable law to any candidate with a disability to allow them to fully participate in the recruitment process. If you have a disability that may require reasonable adjustments, please contact us at reasonableaccommodations@marsh.com.
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.
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