Senior Quantitative Model Developer

Firm Risk Management

Morgan Stanley's Firm Risk Management (FRM) Division is an exciting and rapidly growing space. We support 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.

Morgan Stanley is seeking a quantitative risk associate to join the Firm Risk Management's Risk Analytics Group. Risk Analytics develops market risk, credit risk, climate risk and scenario projection 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.

This role will reside within the Scenario and Credit Stress Analytics (SCSA) department of Risk Analytics. The SCSA department has two main teams. Scenario Analytics is responsible for producing macroeconomic scenarios and forecasts used in Firm‑wide capital planning, budgeting, and loss assessment. Credit Stress Analytics is responsible for developing state‑of‑the‑art credit stress testing and credit loss allowance models.

SCSA is seeking a senior quantitative modeler to join the CSA team. The candidate needs to collaborate within the team and across a range of functional groups to timely fulfill the deliverables for various stress testing exercises.

• Participate in research, development and implementation of credit stress test and credit loss allowances models
• Perform econometric analyses to support methodology development
• Perform backtests, stress tests, scenario analyses and sensitivity studies
• Conduct on‑demand analyses of model changes
• Perform data analyses for various purposes
• Collaborate with teams across the globe

• Master's degree in a quantitative field such as Finance, Economics, Engineering, or Mathematics, or equivalent experience.
• Over 5 years of experience at a financial institution, audit firm, or consulting firm, preferably performing a similar function.
• Strong analytical thinking and problem‑solving skills.
• Proficiency in using Python and R for statistical and econometric analysis.
• Ability to work independently and manage multiple projects simultaneously.
• Attention to detail, a self‑motivated team player who thrives in a fast‑paced, team‑oriented environment.
• Excellent communication skills: ability to present complex and technical issues clearly, both verbally and in writing.

• Knowledge of financial risk management and regulatory compliance.
• Prior risk management experience in the financial industry.

Firm Risk Management values diversity and is committed to providing a supportive and inclusive workplace for all employees.

This role is hybrid and currently requires in office attendance 3 days/week. The in‑office requirement is subject to change at any time.

We are committed to maintaining the first‑class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values – putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back – aren’t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries.

At Morgan Stanley, you’ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work‑life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry.

There’s also ample opportunity to move about the business for those who show passion and grit in their work.

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