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 Firms employees serve clients worldwide including corporations, governments, and individuals from more than 1,200 offices in 43 countries. Firm Risk Management Firm Risk Management (FRM) 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, model and other risks. Job Description: Risk Analytics has an opening for a VP-level person to work on model development. The successful candidate will work extensively with credit risk IRB models. The successful candidate will have strong analytical skills, an excellent work ethic and a high degree of interest in both quantitative and non-quantitative aspects of financial risk management. - Lead modeling efforts for credit risk modelling in Mumbai - Quickly develop a deep understanding of Morgan Stanley's credit risk analytics models. - Participate in research, development, and implementation of credit risk models - Perform econometric analyses to support methodology development - Support backtesting, stress testing, scenario analyses and sensitivity studies - Analyze model changes and perform data analyses for various purposes including model improvement - Partner with teams across Risk Analytics, technology, model risk management, credit risk officers and other teams throughout FRM and the Firm. - Develop, train, oversee and mentor junior staff Relevant Skills - 8+ years of work experience in quantitative modeling, Risk Management, algorithmic trading, global markets or any other quantitative/Data Science field. - Prior work experience with credit markets and products or work experience in a bank credit-related department. Examples include lending, credit trading, origination, underwriting, leveraged finance, CVA. - The candidate needs to be familiar with statistical techniques viz. Regressions Analysis, Hypothesis testing et al. - Understanding of financial institutions regulatory frameworks. Examples include IRB, CECL, CCAR, Dodd-Frank and Basel. - Strong quantitative and analytical skills and ability to work with diverse cultures in a global team. - Strong knowledge of financial products e.g. MBS, CRE, Bonds etc. - Knowledge and hands-on experience in one of the programming languages R, Python, MATLAB, SQL, C or C++ is strongly preferred. - Knowledge of risk mitigation practices and experience with Basel II/III/IV rules will be considered advantageous. - 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. - PRM/FRM, CFA, CQF certification is an advantage.- Experience in AI, ML, NLP, Big Data Analytics, PowerBI is an advantage. Required Qualifications - 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. - Quantitative modeling experience in Finance/ Data Science - Knowledge and hands-on experience in programming languages.
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