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We are looking for an experienced financial quantitative modeller to work on developing and implementing solutions for our insurance and pensions clients. The ideal candidate will be a subject matter expert in the areas of ESG stochastic models & market consistent/risk neutral pricing. Working within the SGS Research team, you will develop modelling solutions for the insurance and institutional asset management sector:
Provide expert quantitative modelling and financial engineering knowledge (e.g. products, practices and regulatory requirements) as input to the team's research and advisory activities.
Provide expert technical support to product management and scrum development team.
Champion our methods and approaches internally and with clients.
Drive the implementation of research and development initiatives in our products. Where appropriate engage in detailed review and development activities to ensure that the team meets its goals.
Work with colleagues in research and product management to prioritise and plan research activities.
Deliver research projects and development initiatives in our financial analytics, risk management, ALM and credit modelling products.
Work and collaborate within a team of quantitave analysts & financial engineers at times taking responsibility for managing & reviewing more junior analysts work
Collaborate with clients and colleagues to develop and deliver innovative research and advisory solutions.
Supporting the sales teams and sales process by providing product knowledge and expertise
The SGS Research team is responsible for the research and development of our stochastic models and calibrations used extensively in the insurance and pensions sectors. The team develops stochastic models and calibrations for use in capital assessment and risk capital management applications, and works with clients on the application of MA's products and techniques. #LI-LA1
A postgraduate degree (ideally PhD) in a numerical discipline.
Broad understanding of modern financial mathematics (e.g. option pricing, hedging, stochastic processes, Monte Carlo simulation, interest-rate modelling)
Significant experience in the life insurance industry, financial software or consultancy, investment bank, or academic research.
Practical experience in the application of stochastic modelling techniques to insurers' valuation, capital and risk management problems; Specific experience in the application of economic scenario generators highly desirable.
Knowledge of insurer's life insurance products, regulation and modelling methodologies.
Stochastic modelling & experience with time series data and large financial datasets.
Strong programming experience (C#, C++, Visual Studio) and ideally some experience with R or MatLab (or similar statistical packages).
Ability to present complex technical solutions in simple terms
Moody's is an essential component of the global capital markets, providing credit ratings, research, tools and analysis that contribute to transparent and integrated financial markets. Moody's Corporation (NYSE: MCO) is the parent company of Moody's Investors Service, which provides credit ratings and research covering debt instruments and securities, and Moody's Analytics, which offers leading-edge software, advisory services and research for credit and economic analysis and financial risk management. The Corporation, which reported revenue of $3.6 billion in 2016, employs approximately 10,700 people worldwide and maintains a presence in 36 countries. Further information is available at www.moodys.com.
Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation or any other characteristic protected by law.
MIS and MSS Candidates are asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.