Principal Modeler / Data Scientist - Noida

Department: Model Development

RMS is the world's leading provider of analytics and decision science solutions for the quantification and management of catastrophic risks throughout the world. RMS models and services are used by hundreds of insurance and reinsurance companies, hedge funds, corporations, and governments to assess a wide-range of natural and man-made perils, from earthquakes and hurricanes to terrorism and disease pandemic.

Job description

We are currently seeking a Principal Modeler / Data Scientist to join our Data Analytics and Solutions Development team in the Model Development group. The team primarily focuses on modeling and developing products related to insured property exposures and loss curves, data and data analytics related applications and solutions. Such products are an important part of RMS product line and provide a wealth of valuable information for our clients.

The candidate will be working in a multidisciplinary environment with other catastrophe risk modelers across different time zones (California, London and India) and would be engaged in the development, design and implementation of a wide range of data products used in catastrophe risk modeling, exposure modeling, valuation modeling and Property & Casualty data quality assessment and enhancement. The candidate will be expected to gain and further utilize an in-depth knowledge of the products and relevant technologies.

The incumbent of this role will be primarily responsible for:

Researching and mining socio-economic and engineering information related to insured properties in different countries.

Job Requirement-

- Developing, evaluating, and implementing methodologies and solutions for property valuation.

- Evaluating the Insurance Policy language in P&C industry in such countries and translating those details to implementable assumptions.

- Developing insured value estimates, deductibles and limits and similar at geographic resolutions such as zip, county, CRESTAs, district, state or similar.

- Executing model testing and implementation.

- Executing analytics of Exposure Data provided by our clients, and benchmarking RMS data products against such data.

- Researching P&C data availability and requirements. Designing, developing and implementing data and data quality assessment related products and solutions.

- Ideal candidate would have independently researched and developed data related products in multiple capacities and would possess strong logical and quantitative analysis skills. The candidate would have 9+ years of hands-on experience in similar roles.

Requirements:

- Education- MS degree in an engineering or science related field including but not limited to: GIS, Civil and Structural Engineering, Financial Engineering, Operations Research, Industrial Engineering, Applied Mathematics, Econometrics, Actuarial Science and Statistics. PhD degree preferred.

- Knowledge of GIS preferred, including experience with ARCGIS and MapInfo software.

- Proficient programming skills in Python or R or similar

- High level of proficiency in data analysis, manipulation and database development software tools (Excel, Access, VBA and SQL).

- Excellent written and verbal skills, as evidenced by white papers or technical presentations at meetings and conferences.

- Experience in one or more of the following would be useful: data mining, developing statistical models, data product development, model testing and implementation.

- Proven record of developing and implementing analytical models is needed. Experience in developing, testing and implementing catastrophe models is an added advantage.

Other Skills:

- Detail-oriented, self-driven quick learner with very strong analytical and problem solving skills, and a high degree of self-motivation.

- Strong organization skills, and the ability to work collaboratively with a team of colleagues across several groups and offices.

- Ability to independently lead, manage and drive projects.

This job opening was posted long time back. It may not be active. Nor was it removed by the recruiter. Please use your discretion.