Senior Specialist

4 weeks ago


Mumbai, India Marsh McLennan Full time

We are looking for a talented and dynamic individual to join our Catastrophe Modelling team at Marsh Mc Lennan. This role is based in Mumbai/Gurgaon This is a hybrid role that has a requirement of working at least two days a week in the office.


We will count on you to:

  • Be the Single point of contact for a specific region or product or line of business
  • Needs to manage large/complex clients with ability to understand all the intricacies of the client requirements
  • Conduct checks and edits on client-supplied data. Produce a detailed exposure profiling. Run catastrophe analyses using (not limited to) RMS, AIR and RQE / commercially available vendor models to estimate potential cat losses
  • Develop in-depth knowledge of the models and manage model uncertainties
  • Provide modelled loss outputs in various forms. Interpret and explain modeling results to colleagues, brokers, clients, reinsurers and other parties
  • Maintain a regular stakeholder interaction & develop relationship with analysts and consultants for constant flow of information on status, exceptions, expectations, forecasts, process changes and new opportunities
  • Independently, communicates with brokers and clients to build strong understanding about the client’s reinsurance buying philosophy and is considered SPOC for the client
  • Be a team player – collaborate effectively with the team by setting standards for performance and motivating to achieve beyond these standards
  • Be a technical SPOC for the analysts and also perform the robust two stage review process
  • Have a view and information on the skills and knowledge gaps of team and plan for training, cross skilling and up skilling of all team members for current and future needs
  • Plan and implement engagement and retention initiatives (including rewards)


What you need to have:

  • 3+ years of experience in Catastrophe Modeling / Risk management


What makes you stand out?

  • Strong academic rigor with degree in Engineering, Mathematics/Statistics or related fields from reputed institution
  • Strong knowledge of stochastic modeling, SQL and geospatial mapping tools like ArcGIS will be highly advantageous.


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 McLennan (NYSE: MMC) is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman . With annual revenue of $23 billion and more than 85,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit marshmclennan.com , or follow on LinkedIn and X.


Marsh McLennan 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, caste, 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.


Marsh McLennan 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 McLennan 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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