Quantitative Analyst (macroeconomic scenario design)
About the position Morgan Stanley is seeking a Risk Quantitative Associate to join the Firm Risk Management's Risk Analytics Group. Risk Analytics develops quantitative models across market risk, wholesale credit risk, counterparty credit risk, and stress testing to help assess and manage the Firm's risk exposures This role sits within the Scenario Analytics (SA) team in the Scenario and Credit Stress Analytics (SCSA) department. The SA team is responsible for developing macroeconomic scenarios and forecasts used in firm wide capital planning, budgeting, and loss assessment. The broader SCSA group builds advanced credit stress testing models that support key risk management and regulatory initiatives. The position offers strong opportunities for professional growth through hands-on modeling work, exposure to large-scale regulatory and internal stress testing exercises, and close collaboration with experienced quantitative professionals. Analysts will build technical expertise in econometric modeling, forecasting, and scenario design, while developing communication and problem-solving skills through cross-functional engagement across the Firm.
Requirements
- Bachelor's degree in a quantitative discipline (e.g., Economics, Finance, Mathematics, Statistics, Engineering, or Computer Science); Master's degree a plus.
- Proficiency in at least one programming language used for analytics (Python preferred); experience with R is a plus.
- 0-5 years of relevant experience in quantitative analytics, risk, model development/validation, stress testing, or a related analytical role (internship experience welcomed).
- Strong quantitative and analytical skills, with the ability to structure problems, validate results, and explain key drivers clearly
- Hands on experience using Microsoft Office tools (e.g. Word, PowerPoint, Excel, Outlook and Teams) for documentation, analysis, presentations, and collaboration.
- Familiarity with statistical/econometric techniques (e.g., regression, time series analysis, forecasting); willingness to learn firm specific frameworks and tools.
Nice-to-haves
- Familiarity with Financial products and financial risk management
- Ability to manage multiple priorities in a deadline driven environment, with strong attention to detail and documentation discipline
- Strong written and verbal communication skills, including the ability to summarize technical work for non technical stakeholders
- Collaborative, proactive, and motivated to learn in a team oriented environment.
- Familiarization of working with version control systems (Git)
- Working knowledge of AI tools