Associate - Algorithmic Trading - Model Risk Management Function - BFSI

Corporate title: Manager & Individual contribution role.

Job summary:

Financial Institutions routinely use models for a broad range of activities including analyzing business strategies, informing business decisions, identifying and measuring risk, valuing exposures or instruments, hedging derivative positions, conducting stress testing, assessing capital adequacy, managing clients assets, informing investment process, measuring compliance with internal limits, maintaining the formal control apparatus of the bank, meeting financial or regulatory reporting requirements and issuing public disclosures. Model Risk arises from the potential adverse consequences of making decisions based on incorrect or misused model outputs and reports, leading to financial loss, poor business decision making, or reputational damage.

As part of the firm's model risk management function, Model Governance Group (MGG) is charged with developing model risk policy and control procedures, performing model validation activities, providing guidance on a model's appropriate usage in the business context, evaluating ongoing model performance testing, and ensuring that model users are aware of the model strengths and limitations.

This role will be within the algorithmic trading MGG team and requires a combination of development and quantitative skills with emphasis on development. This role will focus on conducting quantitative testing of data-driven financial models for the purpose of model validation, as well as developing a testing platform to unify validation of these models across the investment bank.

Core responsibilities:

The successful candidate will be a member of MGG in Mumbai covering algorithmic trading businesses, and will focus on the following activities:

- Work with other model validation quants to understand the testing needs - e.g. backtesting, statistical performance, outlier sensitivity - required to address specific concerns in model validation: model conceptual soundness, reasonability of assumptions, and performance robustness, etc. Coordinate with model development teams to implement necessary testing.

- Collaborate with model development and technology teams and understand their architecture and design a more accessible testing platform that integrates many codebases and databases.

Essential skills, experience, and qualifications:

Strong development skills. BS, Masters, or PhD in Computer Science or Computer Engineering [Math or Engineering with a strong programming expertise is also of interest]. Expertise in Python is a requirement and additional knowledge of Java/C++ preferred. Knowledge of Q is a bonus.

Knowledge of probability, statistical testing, and statistical models. Machine learning is a plus.

Able and willing to learn a variety of technologies and languages, and to implement solutions independently.

Strong written and oral communication skills, the role will requirement collaboration with multiple model development and technology teams.

Knowledge of financial markets and electronic trading is a plus.

One to two years work experience as a developer/quant-developer.