Risk Analytics (Risk Management)
Gender No Preferences
Job Role Others
Career Level Qualified Professional - Experienced
Functional Area Others
Graduation Any Graduation
Post Graduation CFAFRM
Company Name Morgan Stanley
Company DetailsMorgan Stanley mobilizes capital to help governments, corporations, institutions and individuals around the world achieve their financial goals. For over 75 years, the firm’s reputation for using innovative thinking to solve complex problems has been well earned and rarely matched. A consistent industry leader throughout decades of dramatic change in modern finance, Morgan Stanley will continue to break new ground in advising, serving and providing new opportunities for its clients. Morgan Stanley is committed to maintaining the first-class service and high standard of excellence that have always defined the firm. At its foundation are five core values — putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back — that guide its more than 60,000 employees in 1,200 offices across 42 countries.
Morgan Stanley is seeking an Associate/Analyst in its Market Risk Analytics department. The Market Risk Analytics group develops, maintains and monitors the performance of market risk (VaR, Stressed VaR, IRC and CRM) and stress testing models for Morgan Stanley?s portfolio of assets, as required by the regulatory framework and the Firm?s risk management needs.
- Participate in modeling, development and implementation of market risk models
- Collaborate with various Risk departments within the Firm including Market Risk, Credit Risk and Risk IT to deliver model changes and enhancements.
- Perform Quantitative/Econometric Analysis to ensure appropriate modeling and capture of risk, regulatory capital calculation and ongoing compliance with regulatory requirements.
- Collaborate with governance
- Perform backtests, stress tests, scenario analyses and sensitivity studies
- Conduct on-demand analyses of model changes
- Contributing to model implementation & code optimization
- Interacting with quantitative analysts, end-users, business analysts and product owners around the globe (New York, London, Hong Kong, etc.) to gather user stories and clarify requirements
- Owning or contributing to tools development
- Up to 10 years of work experience in quantitative modeling, Risk Management, algorithmic trading, global markets or any other quantitative/Data Science field.
- Understanding of risk management concepts such as VaR (value-at-risk), Stress tests, market risk modelling, derivatives pricing models, Incremental Risk Charge for credit products, back-testing and the risk representation of various portfolios.
- The candidate needs to be familiar with statistical techniques viz. Regressions Analysis, Hypothesis testing, Time-series modeling, Volatility modeling et al.
- Strong quantitative and analytical skills and ability to work with diverse cultures in a global team.
- Strong knowledge of financial traded products e.g. derivatives and their pricing.
- Knowledge and hands-on experience in one of the programming languages R, Python, MATLAB, C# or C++ is strongly preferred.
- Excellent communication skills (Oral and written). Ability to communicate and present logically, precisely and in simple manner, complex and technical issues.
- Attention to details and ability to work under pressure and cope with a fast moving environment.
- Graduate/Under-graduate/Post Graduates/ Advance degrees in finance, mathematics, physics econometrics, engineering or other quantitative subjects.
- Candidates should have a strong theoretical foundation in mathematics, quantitative finance and derivatives.
- Knowledge and hands-on experience in programming languages.
- PRM/FRM, CFA, CQF certification is an advantage.
- Quantitative modeling experience in Finance/ Data Science
- Knowledge of risk mitigation practices and experience with Basel II/III/IV rules will be considered advantageous.
- Experience in AI, ML, NLP, Big Data Analytics, Tableau is an advantage.
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