Quantitative Research - Credit Bond Portfolio - Algorithmic Trading

Our team:

The QR Spread Algo team covers credit, mortgage and public finance flow products. We apply a scientific approach to trading and combine an understanding of credit market structure with modern data analytics to refine sales & trading strategies including workflow automation and automated execution.

The QR Spread Algo team is part of QR Spread which is responsible for developing and maintaining models for valuation, risk, P&L calculations and analysis tools for the Global Spread business. The responsibilities of the team span the full range from new model specification, going through model approval, implementation of model in library, to integration into production systems.

Opportunity:

The opportunity is to join our QR Spread Algo team in Mumbai with a focus on models enhancing trading strategies for corporate bond portfolio transactions.

Key responsibilities could include:

- Development, deployment and support portfolio management strategies including factor models

- Research and back-test tradeable factors through statistical portfolio construction

- Enhance liquidity management of trading desk though execution models

- Development of business intelligence tools including market event detection relevant to portfolio trading

- Written and verbal communication with Model Review Groups in order to make models pass strict in-house standards

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.

Essential skills:

- Very strong in statistics.

- Knowledge of modern techniques such as deep learning is a plus

- Strong OO design skills are required, most likely obtained using C++. In addition, Python would also be a plus as would experience with reactive programming.

- Attention to detail: thorough and persistent in delivering production quality analytics.

- Excellent communication skills; ability to explain her/his thought process clearly as well as communicating efficiently models and strategies behaviors to a non-technical audience.

- Ability to work in a high-pressure environment.

- Pro-active attitude: a self-learner, the candidate should be passionate about problem solving.

- Ideal candidates for these positions would be a graduate/post-graduate from a premier college or institute. A computer science or mathematics background will be most suitable.