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 Quantitative Modeling and Risk Analytics professional with strong technical leadership, analytical judgment, and stakeholder communication skills. The role will lead model development and advanced-analytics workstreams across credit risk, loss forecasting, provisioning, stress testing, capital, and related banking and financial-services use cases.
You will work with Oliver Wyman partners and senior client stakeholders to shape quantitative solutions, guide teams from problem definition through implementation, and translate complex model results into practical business and risk decisions. This role combines hands-on technical depth with workstream leadership, coaching, and client engagement.
Key Responsibilities
Lead end to end model development or independent validation and advanced analytics workstreams across credit risk (PD, LGD, EAD, IFRS 9/ECL), provisioning, stress testing, capital, portfolio analytics, forecasting, and related banking use cases.
Define analytical scope, solution architecture, methodologies, workplans, timelines, and quality standards for complex modeling engagements.
Translate strategic business and risk questions into scalable quantitative solutions and clear decision-oriented insights.
Manage and mentor junior team members, ensuring strong analytical quality, clear documentation, and timely delivery.
Advise clients and internal stakeholders on model strategy, analytical frameworks, implementation choices, performance monitoring, and the integration of models into business and risk processes.
Partner with Oliver Wyman consultants and partners to shape proposals, client conversations, analytics assets, and thought leadership.
Maintain awareness of evolving quantitative modeling, data science, regulatory, and financial-services practices, and translate them into client-ready approaches.
Required Experience and Qualifications
9 to 12 years of experience in model development/validation experience in credit risk quantitative modelling (IRB, CECL, IFRS9, predictive modelling, forecasting models) in consulting or banking roles.
Strong awareness of Model risk Management framework (1LoD, 2LoD and 3LoD in model building activities) and well versed with credit risk related regulation (Basel III/IV, CCAR, CRD-IV, SR 11-7, CP6-22/SS1-23, E23 etc).
Proven experience leading Model Risk Management or financial-modeling workstreams, including solution design, methodology, data, implementation, performance assessment, documentation, and stakeholder engagement.
Bachelor’s or master’s degree in Statistics, Mathematics, Economics, Finance, Engineering, Computer Science, Data Science, or another quantitative discipline; advanced degree preferred.
Strong technical knowledge of statistical modeling and financial-services applications, including credit risk, forecasting, provisioning, stress testing, capital, and portfolio analytics.
Hands-on proficiency with Python and SQL, with the ability to review and guide technical implementation; experience with SAS, R, Spark, cloud platforms, or large-scale data environments is an advantage.
Deep ability to select and evaluate modeling approaches, statistical assumptions, performance metrics, limitations, overlays, expert judgment, and business-use alignment.
Strong project management skills, including ability to manage multiple workstreams, deadlines, and stakeholders.
Excellent verbal and written communication skills, with the ability to translate complex models and analytical findings into practical business and risk implications.
What We Look For
Strong analytical judgment and comfort challenging model assumptions.
Leadership presence with the ability to build trust with clients and internal teams.
Practical, impact-focused problem solving.
Strong coaching mindset and commitment to developing India-based analytics talent.
Ability to balance technical depth with commercial and client context.
Comfort working with global teams across time zones and traveling when required.