Analyst, Model Success

RMS

Jun 1, 2023

Applications are closed

Job
Full-time
Entry Level
Data
London

Requirements

Our analysts all demonstrate exceptional potential to thrive in an environment which demands strong teamwork, technical aptitude, and dedication to our clients and their needs. As an analyst in the Model Success team, you:
Put others first. You are motivated by the desire to help other people succeed.
Enjoy solving problems. You relish the challenge of solving analytical and technical problems with and for other people.
Are driven to achieve great outcomes. You prioritize what is of greatest impact and understand when a job is done.
Are a strong communicator. You communicate effectively verbally, in writing, and in presentations.
Make the complex simple. You articulate technical or scientific concepts clearly to varied audiences.
Love to learn. You demonstrate a constant desire and broad capacity to learn new skills and concepts.
Want to play your part. You have an interest in the role of science and technology in understanding and managing the natural and man-made risks facing society.
Required Qualifications:
BS or MS degree in any of the following disciplines or related fields:
Mathematics, engineering, physics, statistics, economics
Earth or climate sciences (including geology, geophysics, seismology, meteorology)
Risk management, insurance
Exceptional written and verbal communication skills in English

Responsibilities

As an analyst in the Model Success team:
You’ll play an active role in delivering frontline support to our global client base, working directly with customers and internally across multiple teams.
Your work will span all our products and the markets we serve, including our suite of world-leading catastrophe models, from hurricanes to cyber-attacks.
You’ll develop technical knowledge, enhance your problem-solving and data manipulation skills, and cultivate the communication skills required to advise clients with confidence.
Your career:
As one of our entry-level analysts you are central to our future, and we provide a training program that equips you with the breadth and depth of education and experience to have a successful career.
Your first 6 weeks will comprise a mix of classroom and on-the-job training.
Over the next few years, as you progress in your career within the team, you will have the opportunity to attain more specialised knowledge in a subset of topic areas and take on more responsibility in the following areas:
Resolving more complex requests, which may involve working directly with Subject Matter Experts in other teams
Leading the facilitation of client training sessions and handling more sensitive client communications
Helping more junior team members to develop and coordinate client work that involves multiple contributors
Providing deeper levels of input into larger client project work (weeks to a few months timeframe)

RMS

Technology

Industry

1001-5000

Employees

1988

Founded Year

Mission & Purpose

For over 30 years, Risk Management Solutions (RMS), a Moody's Analytics company, has helped to pioneer the catastrophe risk industry. RMS models underlie the nearly US$2 trillion Property & Casualty industry and many insurers, reinsurers, and brokers around the world rely on RMS model science. We continue to lead in innovation by combining advanced science with technology. We build comprehensive risk models, software, SaaS technology, cloud-based applications, and APIs to help insurers, reinsurers, financial services organizations, and the public sector outperform by evaluating, and managing global risk. Leaders across multiple industries can address the risks of tomorrow through RMS Risk Intelligence™ (RI)—our open, unified cloud platform for global risk—enabling them to tap into RMS HD models, rich data layers, intuitive applications, and APIs. Further supporting the industry's transition to modern risk management, RMS spearheaded the Risk Data Open Standard (RDOS), a modern, open-standard data schema designed to be an extensible, flexible, and future-proof asset within modeling/analysis systems.