What we do
Structured Finance & Lending (SFL) Strats Team within Global Markets Division (GMD) is responsible for modeling and pricing of structured trades, as well as building risk management tools for SFL businesses and clients using cutting edge quantitative, machine learning, and other AI techniques. The business focuses on providing customized financing solutions to clients, which covers a wide range of collateral asset classes such as private credit and equity, capital calls or specialty assets, in the forms of Loans, Repurchase Agreements (Repos), Asset-Backed Securities and Derivatives. This role offers a unique opportunity to work within the Structured Financing and Lending businesses to deliver tailored solutions to our clients while gaining exposure to a wide range of asset classes.
Your Impact
SFL Strats play a critical role in deal structuring, pricing, execution and risk management. This is a highly visible platform to put quantitative skills and knowledge in use to make a direct impact on business growth. You will gain familiarity with different asset classes & risk factors while working on various trades and projects and build a broad foundation of product knowledge.
Responsibilities
Improve existing pricing models and create new ones for structured products. Understand transaction risks and analyze drivers of profits and losses. Provide analysis for new transactions. Drive commercial outcomes using data. Improve existing and create new models for the pricing and analysis of derivatives, public/private market assets and transactions Identify, curate, and integrate new structured and unstructured datasets into models. Build end to end solutions from data collection to automated actions.
Who We Look For
Strong quantitative and coding skills with desire to develop commercial mindset Solid work ethics, team oriented, high levels of motivation. Ability to work in fast-paced environment and time-sensitive situations. Effective communication skills in verbal and writing to both technical and business audience.
Basic Qualifications
Excellent academic record in a relevant quantitative field such as Mathematics, Physics, Engineering or Computer Science. Strong math and quantitative skills Experience in object-oriented programming with a language such as C++, Java or Python. Knowledge of Stochastic calculus and derivatives pricing, or Machine Learning background Knowledge of credit market and products, interest rates, FX, or risk management is preferred.
