Moody's Analytics calls this role internally Associate Economist 1 / 2.
Risk modelers are directly involved in the development of Moody’s Analytics risk modelling solutions and consulting client projects with major banks and other financial institutions worldwide.
Being a part of truly global Moody’s Analytics team, risk modelers contribute to client and internal projects in every phase, including preparing and delivering presentations, data analysis, methodology design, model development and enhancement, documentation writing, and results delivery.
We are looking for highly motivated individuals with strong quantitative skills combined with excellent communication skills, willing to collaborate, learn and develop in a very dynamic and multicultural environment.
Consulting work with major financial institutions and other industry players worldwide;
Acting as part of the team that develops risk models;
Risk modelling, including the data analysis, development, documentation, implementation, and validation of risk models using state of the art statistical and econometric techniques;
Delivering presentations and workshops for various internal and externals audiences;
Participation in internal workshops aimed at enhancement of model building techniques employed by Moody’s Analytics;
Screening regulatory and industry developments in order to remain up-to-date on leading challenges and trends on the market;
Emphasis is on consumer credit with some exposure to other forms of risk modeling in partnership with other departments within Moody's Analytics;
The Economic and Consumer Credit Analysis team, a division of Moody's Analytics, is a leading independent provider of economic, financial, country, and industry research designed to meet the diverse planning and information needs of businesses, governments, and professional investors worldwide.
Our research has many dimensions : country analysis; financial markets; industrial markets; and regional markets. Moody's Economy.
com information and services are used in a variety of ways, including strategic planning; product and sales forecasting; risk and sensitivity management; and as investment research.
Strong academic background Ph.D. or Master’s degree in Statistics, Mathematics, Physics, Data Science, Economics or other closely related field from a top school is essential.
Advanced programming skills in R, STATA, SAS and / or Python.
Knowledge of quantitative techniques and the ability to communicate technical subject matter clearly and concisely.
Industry experience in quantitative risk modelling and / or knowledge of banking regulations in the areas of credit risk, capital adequacy and stress-testing is preferred.
Excellent presentation, writing, time management and interpersonal skills are required.
Highly organized and efficient.
Excellent attention to detail.
Ability to work using own initiative and without close supervision.