Quantitative Analyst

Overview

Company Profile

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm's employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices in 43 countries.

As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.

Firm Risk Management

Morgan Stanley's Firm Risk Management (FRM) Division is an exciting and rapidly growing space. The division supports Morgan Stanley to achieve its business goals by partnering with business units across the Firm to realize efficient risk-adjusted returns, acting as a strategic advisor to the Board and protecting the Firm from exposure to losses as a result of credit, market, liquidity, operational, model and other risks.

Background on the Position

The role will reside within the Risk Analytics department in the Firm Risk Management division. Risk Analytics develops market risk analytics, credit risk analytics and scenario analytics models providing quantitative analysis on the Firm's risk exposures. By developing mathematical and statistical models, Risk Analytics calculates the risks associated with specified sets of financial positions and day-to-day operations.

Morgan Stanley is seeking an Associate in its Market Risk Analytics department with focus on Credit asset class. The Market Risk Analytics group develops, maintains, and monitors the performance of market risk (VaR, Stressed VaR, and IRC) and stress testing models for Morgan Stanley's portfolio of assets, as required by regulatory frameworks and the Firm's internal risk management needs. The new hire will join the Market Risk Analytics Credit team to undertake research, analysis, modelling, and implementation of various market risk models pertaining to Credit products to ensure appropriate modelling and capture of risk, regulatory capital calculation, and ongoing compliance with regulatory requirements, including the upcoming Fundamental Review of Trading Book (FRTB).

The position will play a key role both in the maintenance of current models and further enhancements as required from time to time. The role will be an opportunity for a candidate who wishes to work on all aspects of a model's lifecycle
- Development, Implementation, Testing, Calibration, Internal and Regulatory submission, and Periodic Performance Monitoring.

• Performing quantitative analysis on various aspects of Market Risk models like VaR, Stressed VaR, Risk Not in VaR for Credit products (e.g. Bonds, CDS, Traded loans, etc.)
• Developing and enhancing models for changing internal risk management needs, new regulatory requirements (e.g., FRTB), or improvements in capturing the risk
• Actively participating in code development for the purpose of model implementation, model performance monitoring, and for performing different analyses
• Analyze, understand, and explain changes in risk metrics driven by model updates and position changes
• Analyzing model performance metrics
• Interacting with stakeholders from various departments like Front Office strategists, Market Risk Managers, Model Risk Management and FRM IT
• Participating in documentation of model methodologies and implementation
• Responding to queries from Model Risk Management, Internal Audit, and regulators

• Requires a degree in Quantitative Finance, Math, Statistics, Computer Science, Physics, Engineering, Economics or a related field of study (Masters/PhD highly preferred)
• Strong Quantitative skills
• Strong Python coding skills (essential), knowledge of database querying functionalities/languages
• Familiarity with statistical modelling, Monte Carlo, Historical Simulation
• Knowledge of financial products with Credit factors will be…