Analyst, Model Success

Within Model Success, Regulatory Analytics focuses on projects that concern the generation and interpretation of model output used to support Moody’s RMS submissions to various regulatory bodies.


Date posted

Feb. 23, 2023 3:30 pm

Application deadline

Mar. 23, 2023 5:00 pm


Moody's Risk Management Solution


  • United States

Job description

The Regulatory Analytics team sits within Moody’s RMS’ broader Model Success organization which itself works for both internal and external clients, helping them to better understand, interpret, and accept the output and workings of RMS models. Within Model Success, Regulatory Analytics focuses on projects that concern the generation and interpretation of model output used to support Moody’s RMS submissions to various regulatory bodies. We are a small team of fun, intellectually curious, and results driven individuals whose projects require that we possess:

  • Data analysis and coding skills necessary to extract, organize, and visualize results from large datasets 
  • Catastrophe modeling and physical science knowledge needed to interpret results and understand what drives them
  • Communication skills to explain key findings to audiences from a variety of backgrounds

Our team has a presence on both the East and West coast of the U.S. and this role could be based in either the Hoboken or San Francisco Bay Area Moody’s RMS offices. If you enjoy a challenge and are looking to develop yourself across a broad set of skills in an exciting and interesting business, then this role is for you. 

The Person:

  • Someone who enjoys using their superior critical thinking, time management and planning skills as well as a keen attention to detail to take on new challenges and develop solutions for a variety of interesting projects
  • Someone who can effectively work independently but can also work collaboratively as a part of a multi-disciplinary team
  • Someone with strong interpersonal, communication, and presentation abilities who can communicate complex topics to audiences of varying technical backgrounds and business functions
  • Someone who wants to apply their technical background in physical science and/or coding to a variety of practical business applications
  • Someone who can comfortably and confidently handle occasional periods of highly time sensitive and business critical work 


  • Working with and learning from senior colleagues, develop broad knowledge of Moody’s RMS catastrophe models; grasp the fundamental science and methodological philosophies underpinning the models and learn to apply this knowledge to interpreting model output and behavior. Eventually look to use these skills to lead regulatory projects on your own.
  • Learn about Moody’s RMS software and the database infrastructure that Moody’s RMS models use to output data. Using this knowledge and with the guidance of senior colleagues, develop well written and documented computer code that generates the data analytics and visualizations required for Moody’s RMS regulatory submissions. Create and maintain detailed supporting documentation of this code as required by certain regulatory bodies.
  • Present to external parties such as representatives of regulatory bodies or internal parties such as Moody’s RMS Model Development and Product Management team members to summarize and contextualize key findings from analytics that you create. Additionally, be able to provide a non-technical summary explaining the results and/or the algorithm used to create said results
  • Learn about Moody’s RMS as an organization and over time come to possess an understanding of the primary regulatory bodies Moody’s RMS works with. Additionally, work with colleagues across the wider Model Success team to learn about Moody’s RMS customers and how/why they use Moody’s RMS models.

 Experience Required:

  • Possess a BS/MS/PhD in one of the following disciplines or a related field:
    • Meteorology, Atmospheric Physics
    • Hydrology
    • Geology, Geophysics
    • Chemistry, Biology
    • Seismology
    • Forestry
    • Mathematics
    • Data Science
  • Familiarity with at least one coding language (preferably R)
  • Experience using computer code and other data mining tools to pull relevant information out of large datasets
  • Possess excellent time management, communication (written and verbal), problem solving and troubleshooting skill sets
  • Be self-driven and able to perform well within cross-functional, multi-organizational, and virtual teams


  • Experience using version control software such as GitHub
  • Experience using Microsoft SQL Server or similar database management tools
  • Experience working with large, complex datasets
  • At least one year of relevant professional experience


Risk Management Solutions, Inc. (RMS) models and solutions help insurers, financial markets, corporations, and public agencies evaluate and manage global risk throughout the world. RMS has some 1,300 employees across 13 offices in the US, London, Bermuda, Zurich, India, China, Japan, Singapore, and Australia, with products and models covering six continents.

We lead an industry that we helped to pioneer—catastrophe risk modeling – and continue to innovate. In May 2019, we announced the launch of RMS Risk Intelligence™ (RI), an open, flexible and future-proof platform for strategic risk management. Through this purpose-built platform, clients can tap into RMS HD models, rich data layers, intuitive applications and APIs that simply integrate into existing enterprise systems to support business decisions across underwriting, risk selection, mitigation and portfolio management.

Insurers, reinsurers, trading companies, and other financial institutions trust RMS solutions to better understand and manage the risks of natural and human-made catastrophes, including hurricanes, earthquakes, floods, terrorism, and pandemics.

Visit to learn more and follow us on LinkedIn and Twitter

RMS is proud to be an equal opportunity workplace. We are committed to equal employment opportunity without regard to race, color, creed, gender, religion, marital status, registered domestic partner status, age, national origin or ancestry, physical or mental disability, genetic characteristics, sexual orientation, or any other classification protected by applicable local, state, or federal law.


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