Location
In office (Hyderabad)
Seniority
Middle
Confirmed on the employer's own hiring board on Nov 3, 2026. First seen by Alion on Nov 2, 2026. Verisk scores A on the Alion truth index.
Overview
Company
Impact
Profile match
Verisk Analytics provides data analytics and risk models for the insurance industry. Its catastrophe models, claims data and rating services underpin much of property underwriting. The company also supplies fraud detection and climate risk analytics.
Backed by Comcast Ventures
We are seeking a Research Engineer II to develop and enhance catastrophe risk models that assess the vulnerability of buildings and infrastructure to wind, hail, snow, and freezing temperatures.
Based in Hyderabad, you will apply structural engineering, probabilistic modelling, and programming to estimate physical damage and financial losses. You will collaborate with multidisciplinary research teams, validate model results, and communicate findings to internal stakeholders and external clients.
- Acquire and analyse building inventory, damage, insured loss, and insurance claims data to understand vulnerability across global regions.
- Work with proprietary datasets and integrate relevant insights into catastrophe risk models.
- Develop vulnerability functions and monetary loss curves for structural and non-structural components of buildings and infrastructure.
- Assess the effects of wind, tornadoes, hail, and snow on building and infrastructure performance.
- Implement research findings through loss simulation code and analytical tools.
- Validate model outputs and probabilistic risk assessments.
- Use GIS and related tools for data analysis and visualisation.
- Conduct real-time and virtual building damage assessments during and after significant natural catastrophe events.
- Prepare technical documentation, publications, and client-facing materials.
- Present research methods and findings to internal teams and external clients.
- Ph.D. in Civil Engineering with a special emphasis in Structural Engineering.
- Experience in performance-based design, probabilistic and stochastic risk assessment and modelling, and reliability theory applied to structural engineering.
- Proficiency in C/C++ and Python, along with working knowledge of R, MATLAB, and Microsoft Office.
- Ability to apply engineering principles to complex structural engineering and risk assessment problems.
- Ability to conduct independent research and collaborate within a multidisciplinary team.
- Excellent written and verbal communication skills.
- Strong organisational and documentation skills, with close attention to detail.
- Knowledge of GIS applications, such as ArcView, and SQL Server is a plus.
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