About Oliver Wyman
At Oliver Wyman, a Marsh (NYSE: MRSH) business, we bring deep industry insight, bold innovation, and a collaborative approach that cuts through complexity to help organizations navigate their most defining transformative moments.
As a business of Marsh, we work alongside the world’s leading experts across risk, reinsurance and capital, people and investments, and management consulting. Together with Marsh Risk, Guy Carpenter, and Mercer, we help organizations build resilience and competitive advantages from every angle. With annual revenue over $24 billion and more than 90,000 colleagues in 130 countries, Marsh helps build the confidence to thrive through the power of perspective.
For more information, visit oliverwyman.com, or follow us on LinkedIn and X
About Data and Analytics (DNA) Practice
At Oliver Wyman Data and Analytics, we partner with clients to solve tough strategic business challenges with the power of analytics, technology, and industry expertise. Our India DNA team brings high-quality analytics and quantitative talent into global consulting engagements, delivering practical, client-ready solutions across financial services and other priority sectors.
Role Summary
We are looking for a senior AI and Generative AI professional with strong technical depth, delivery leadership, and client-facing communication skills. The role will focus on leading AI / GenAI solution design, evaluation, governance, and implementation across client use cases such as knowledge assistants, document intelligence, workflow automation, decision support, advanced analytics, and responsible AI transformation.
You will work with Oliver Wyman partners, consultants, and senior client stakeholders to identify high-value AI opportunities, shape solution architecture, lead delivery workstreams, manage technical quality, and translate complex AI topics into practical business recommendations. This is a hands-on leadership role suited for someone who can balance technical depth, commercial judgment, and team development.
Key Responsibilities
Lead AI, machine learning, and GenAI workstreams from use-case discovery and solution design through prototyping, evaluation, deployment readiness, and adoption support.
Define technical scope, delivery approach, architecture options, workplans, quality standards, and success metrics for complex AI / GenAI engagements.
Partner with clients to identify high-value AI opportunities, assess feasibility, prioritize use cases, and translate business needs into data, model, platform, and governance requirements.
Lead development and review of GenAI applications such as RAG knowledge assistants, document intelligence solutions, enterprise copilots, workflow agents, semantic search, summarization / extraction tools, and prompt-driven analytics.
Advise on model and platform choices, including commercial LLMs, open-source models, small language models, vector databases, cloud AI services, integration patterns, and build-versus-buy considerations.
Oversee experimentation, prompt engineering, retrieval design, fine-tuning / adaptation approaches, benchmarking, model evaluation, performance monitoring, and issue remediation.
Establish responsible AI, LLMOps, MLOps, model governance, privacy, security, human-in-the-loop, auditability, and monitoring practices for AI-enabled solutions.
Review code, solution designs, documentation, demos, technical findings, and client deliverables to ensure analytical quality and client readiness.
Manage and coach junior team members, ensuring strong problem structuring, engineering discipline, documentation quality, and timely delivery.
o Partner with Oliver Wyman consultants and partners to shape proposals, client conversations, reusable assets, and thought leadership on AI and GenAI.
Required Experience and Qualifications
9 to 12 years of experience in AI / ML, data science, GenAI engineering, NLP, software engineering, data engineering, advanced analytics, AI strategy, or related consulting / technology roles.
Proven experience leading AI / GenAI or advanced analytics workstreams, including solution design, data assessment, model evaluation, technical delivery, documentation, and stakeholder management.
Bachelor's or master's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Economics, AI / ML, or another quantitative or technical discipline; advanced degree preferred.
Strong technical knowledge of machine learning, NLP, LLMs, embeddings, RAG, agents, prompt engineering, fine-tuning, model evaluation, model monitoring, and AI application architecture.
Hands-on proficiency with Python and SQL; experience with cloud platforms, APIs, MLOps / LLMOps tools, orchestration frameworks, and large-scale data environments is an advantage.
Ability to assess model performance, solution reliability, data quality, hallucination risk, bias / fairness, explainability, limitations, controls, and business-use alignment.
Experience writing and reviewing senior-stakeholder-ready technical documentation, implementation plans, governance materials, and client deliverables.
Strong project management skills, including ability to manage multiple workstreams, deadlines, risks, stakeholders, and junior team members.
Excellent verbal and written communication skills, with the ability to translate complex AI / GenAI topics into practical business, risk, and technology implications.
Preferred / Valued Experience
Experience delivering enterprise AI / GenAI solutions in regulated or complex environments such as financial services, insurance, risk, finance, operations, customer service, or knowledge management.
Experience developing or reviewing responsible AI frameworks, AI governance policies, LLM evaluation standards, model risk controls, monitoring frameworks, and remediation plans.
Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, OpenAI-compatible APIs, Hugging Face, LangChain, LlamaIndex, vector databases, MLflow, Databricks, Snowflake, Spark, or Kubernetes.
Experience scaling AI prototypes into production-ready products, including integration design, security review, testing, change management, adoption tracking, and value measurement.
Consulting experience or experience in client-facing AI, analytics, product, technology, or transformation roles.
Experience shaping proposals, solution blueprints, accelerators, thought leadership, or commercial discussions around AI and GenAI.
What We Look For
Leadership presence with the ability to build trust with clients and internal teams.
Practical, impact-focused problem solving grounded in technical depth.
Strong coaching mindset and commitment to developing India-based analytics and AI talent.
Ability to balance hands-on delivery with architecture, governance, and commercial context.
Curiosity about emerging AI techniques with sound judgment about risk, quality, and adoption.
Comfort working with global teams across time zones and traveling when required.
Skills Required
- 9 to 12 years of experience in AI/ML, data science, Generative AI engineering, NLP, software engineering, data engineering, advanced analytics, AI strategy, or related consulting or technology roles
- Experience leading AI, Generative AI, or advanced analytics workstreams, including solution design, data assessment, model evaluation, technical delivery, documentation, and stakeholder management
- Bachelor's or master's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Economics, AI/ML, or another quantitative or technical discipline
- Strong technical knowledge of machine learning, NLP, LLMs, embeddings, RAG, agents, prompt engineering, fine-tuning, model evaluation, model monitoring, and AI application architecture
- Hands-on proficiency with Python and SQL
- Ability to assess model performance, reliability, data quality, hallucination risk, bias, fairness, explainability, limitations, controls, and business alignment
- Experience writing and reviewing senior-stakeholder-ready technical documentation, implementation plans, governance materials, and client deliverables
- Strong project management skills across multiple workstreams, deadlines, risks, stakeholders, and junior team members
- Excellent verbal and written communication skills, including translating complex AI and Generative AI topics into practical business, risk, and technology implications
- Experience delivering enterprise AI or Generative AI solutions in regulated or complex environments
- Experience with responsible AI frameworks, AI governance policies, LLM evaluation standards, model risk controls, monitoring frameworks, and remediation plans
- Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, OpenAI-compatible APIs, Hugging Face, LangChain, LlamaIndex, vector databases, MLflow, Databricks, Snowflake, Spark, or Kubernetes
- Experience scaling AI prototypes into production-ready products
- Consulting or client-facing AI, analytics, product, technology, or transformation experience
- Experience shaping proposals, solution blueprints, accelerators, thought leadership, or commercial discussions around AI and Generative AI
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.
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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.
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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.
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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
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.









