Sr. Analyst - Catastrophe Modeling

Job type: Permanent
Salary: ₹1,000,000.00
Contact name: Nishant Sharma

Contact email:
Job ref: 35245
Published: 15 days ago
Startdate: 04/09/2021

Job opportunity in Mumbai for a professional holding at least 2-4 years' experience in CAT Modelling. You will use your experience to help clients better understand their overall exposure to catastrophe risk and allow them to plan accordingly. 

If this sounds exciting, apply with us! 



A leading, global group with a strong foothold in specialty financial services serving millions of customers across the full spectrum.  


  • Handling the data in terms of exposure, assessing of data quality while making necessary improvements. 
  • Recording and communicating assumptions made before data analysis, generating the reports that showing changes in data and relate the impact on CAT model results 
  • Hands on exposure in CAT Modelling models and reporting the results in relevant client’s business 
  • Interpreting the change in loss results due to modelling parameters and client exposure change 
  • Examining the results and measuring the risks happening due to application changes in models/application of reinsurance alternatives. 


  • At least 2 to 4 years of experience in CAT Modelling in providing analytics at account or portfolio level 
  • Degree in Mathematics/Statistics/Computer-Science/Engineering or related fields 
  • Basics of Insurance/Reinsurance/CAT Modelling training  
  • Hands on exposure in at least one of the CAT Modelling software RMS/ AIR/ RQE  
  • Familiarity in Excel, Access and SQL 


  • An opportunity to define, lead and coordinate the operations of the company. 
  • Work in a fast-paced environment  
  • An opportunity to work with a blue–chip firm in a high visibility role  


If you think that this role will add value to your career, kindly write me an email along with your updated CV on


We are an equal opportunity recruitment firm and value diversity in the talent we identify for our clients. We do not discriminate on the basis of race, religion, colour, origin, gender, sexual orientation, age, marital status, veteran status, or disability status.