The Credit Technology quantitative development team works closely with the Credit Risk Management & Analysis business group to create quantitative tools and analyses, which measure and explain the Firm's counterparty risk. The team is responsible for the development of Monte-Carlo based Potential Exposure models, which are used for credit risk management of trading positions, client margining, management reporting, and regulatory capital calculations. The team is involved in the complete software development life-cycle including prototyping, requirements, design, implementation, testing, deployment, and maintenance.
Members of the team are exposed to a broad array of financial products, pricing, and risk models.
Develop, document, and validate Potential Exposure models.
Develop new credit risk measurement tools and extend existing ones.
Perform quantitative risk analysis and communicate the results to the business and technology.
Investigate, analyze, and understand the Firm's desk pricing models across a wide variety of instruments and products.
A successful candidate will have:
Strong programming ability.
Demonstrated analytic and quantitative ability. For example, a graduate degree in science or engineering.
Strong written and verbal communication.
Ability to learn new things quickly and work independently.
Desire and ability to play on a team and learn new things every day.
A candidate should also have at least one of the following:
Experience in the full software life-cycle and a proven track record of delivering successful software projects.
Experience working on large code bases and systems (> 1 million lines of code).
Experience programming in Python, Matlab, Smalltalk, Lisp, or a similar language.
Knowledge of derivative pricing in one or more product areas.
Knowledge of probability, statistics, time series analysis, or Monte-Carlo simulations.
Knowledge of quantitative finance and risk management.
A Major Global Financial Services Firm based in New York City.
Interested candidates should contact Ms. Ellen Parsons directly at email@example.com, or www.linkedin.com/in/ellenmparsons/