Lead Quantitative Analytics Specialist ( Vice President) - Model Risk Management, Markets Division: Electronic Trading and Derivatives

About this role:

Model Risk Management (MRM): The Model Risk Management team is responsible for end-to-end oversight and risk management of models used across the enterprise. This includes the assessment and mitigation of risk created by models throughout the model lifecycle including Development, Validation, Usage and Ongoing Monitoring. 

Markets division of MRM is responsible for the validation, performance monitoring and oversight of models used in trading, market and counterparty risk management. These models are used to price and hedge trading (including derivatives and fixed income) transactions, as well as to measure the risk of possible economic loss from adverse changes in market risk factors such as equity and commodity prices, interest rates, credit spreads, foreign exchange rates, mortgage rates, market liquidity dynamics, or counterparty defaults. Markets MRM is also responsible for models specifically designed for electronic trading activities including signal models and order execution strategies.

Markets MRM is seeking an experienced analyst to join a multi-asset team whose model coverage include Commodities and Equities Derivatives, as well as Electronic Trading Signals and Strategies.  Our diverse coverage offers a world of opportunity to expand your capabilities and advance your career. We invest in our people and provide a supportive environment in which to learn and grow.

The main responsibility of the successful candidate will be to provide risk assessment of models throughout their lifecycle. This requires an inquisitive mindset and a willingness to challenge (even established) modeling choices and assumptions, to design relevant testing scenarios, to numerically implement model components, to conduct and analyze comprehensive testing, and to develop alternative models. Each of these steps needs to be executed and documented with risk-based rationale to support or invalidate modeling choices, assumptions and adequacy in the context of the model purpose and usage.

This highly visibly position will provide interaction with various key model stakeholders and therefore requires someone with the ability to develop and maintain strong strategic partnerships.  The ability to communicate with different audiences (technical staff, senior management, regulators) both verbally and in writing is very important.  The team operates in a fast-paced environment and the ability to multi-task and meet strict timelines is critical.

In this role, you will:

• Perform model validations and clearly documenting narrative of validation perspective

• Provide effective challenge to models developed in the lines of business (LOB)

• Develop alternative benchmarking models or replicating LOB models

• Reduce model risk to meet or exceed regulatory and industry standards

• Identify conceptual weaknesses in a model and understanding tradeoffs with other approaches

• Communicate model issues and limitations to key stakeholders

• Contribute to improvement of model building and use practices

• Provide leadership and consultation to less experienced validators

• Provide analytical support and offering insights regarding a wide array of business initiatives

• Interact with senior management and regulators on key modeling issues, including the identification, management and mitigation of model risk

• Communicate to different audiences (other technical staff, senior management and regulators) both verbally and in writing

• Manage relationships with key model stakeholders

Required Qualifications:

• 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Desired Qualifications:

• PhD in quantitative field such as Mathematics, Statistics, Engineering, Physics, Economics or Computer Science.

• Relevant experience in model development, research, or validation in the areas of electronic trading, financial derivatives, market risk, or counterparty credit risk at financial institutions, software companies, teaching/research institutions, or other related entities.

• Familiarity with statistical data analysis and machine-leaning models

• Knowledge of stochastic processes, stochastic calculus, Monte Carlo methods, numerical methods (finite differences, optimization…)

• Hands-on object-oriented coding experience (Python, C++ and Java are most relevant)