Senior Specialist - Catastrophe Modelling

We are seeking a talented individual to join our Catastrophe Modelling team at Guy carpenter. This role will be based in Noida. This is a hybrid role that has a requirement of working at least three days a week in the office. Senior Specialist - Catastrophe Modelling We will count on you to:

• Ensure smooth and timely delivery with utmost quality for all the Marsh clients across the globe by providing Cat Analytics support using the models RMS/AIR/RQE
• Assist with quality check of Cat Modeling deliverables.
• Assist with Cat modeling R&D projects to further develop knowledge on model methodologies.
• Challenge the status quo on the existing ways of working and propose new ways to achieve more efficiency
• Proactive interaction with stakeholders on modelling requirements and ad-hoc requests.
• Provide mentorship and training to new joiners and junior team members.
• Provide insights and process improvement ideas to enhance the efficiency of the process.
• Respond to brokers, clients and stakeholders on queries relating to reconciliation of outputs for Nat Cat.
• Build internal documentation and presentations around process specifications and capabilities.

What you need to have:

• Degree in Engineering/Mathematics/Statistics or related fields
• 2.5-4 years of experience that incorporates Cat modeling expertise - specifically with established industry models (RMS, AIR etc.) tools on a regional or global basis across the major perils
• Working knowledge of stochastic modeling, R, Python with proficiency in SQL and geospatial mapping tools like ArcGIS will be highly advantageous
• Client and project delivery experience – demonstrated ability to present, communicate, and deliver technical content to internal stakeholders and external clients on complex subject matter
• Collaboration experience - working in multi-disciplinary teams of risk engineers, actuaries, catastrophe modelers an added plus

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.
• Exposure to working with Actuaries and RFO team

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.