Job Description

Our team

The Credit QR team is responsible for developing and maintaining models used for quoting and market making, as well as valuation, risk, P&L calculations, for the Global Credit business. The responsibilities of the team span the full range from new model specification, going through model approval, ensuring compliance with internal policies and industry regulations, implementation of model in library, to integration into market-making, risk and P&L systems as well as their day-to-day support.

Opportunity

This opportunity is to join our Credit QR team in New York as an Associate or a VP depending on experience, with a focus on models used in the Credit Index Market Making business. While the focus is on Algorithmic Market-Making models used for Credit Indices and Credit ETFs, there is an opportunity to work on Pricing and Risk-measurement models used for Credit Exotics and Hybrids as well. Candidates directly from university will be considered.

Key responsibilities could include:

* Development, deployment and support of production code for market-making models in our in-house systems
* Research and development into models used for market-making and quoting strategies
* Applying machine learning and statistical techniques to analyze market moves and trade data
* Working with the Trading Desk, e.g., explaining model behavior, carrying out scenario analyses, developing and delivering business intelligence tools, and supporting analytics
* Working with Technology on ongoing improvements to the existing infrastructure, as well as liaising on roll-out of new analytics
* Writing model documentation compliant with internal and regulatory standards and working with the Model Review teams to facilitate timely and efficient review and approval of models

Requirements

We work in a very dynamic environment, and excellent communication skills are required in our interaction with trading, technology, and control functions. A healthy interest in good software design principles is essential. The role requires a detailed understanding of Credit Derivatives and Credit Markets. It is understood that the candidate may not have this knowledge from previous experience, but the successful candidate would be highly motivated to gain this knowledge. A Ph.D. in a numerate subject from a top academic institution is highly desirable, but not an absolute requirement.

Essential skills:

* Strong Quantitative Modeling ability as well as familiarity with time-series modeling is required
* Strong OO design skills are desirable, preferably obtained using C++. Extensive Python experience would be a plus
* Strong Data Science background, specifically Deep Learning or Reinforcement Learning, would be an advantage
* Attention to detail: thorough and persistent in delivering production quality analytics
* Excellent communication skills; explains her/his/their thought process clearly and communicates models and strategies to a non-technical audience efficiently
* Ability to work in a high-pressure environment
* Have good work-ethics, be motivated, pro-active, and a team-player. A self-learner, the candidate should be passionate about problem solving and should have a strong interest to learn about our Business, Models and Infrastructure