Director - Credit Risk Modeling (Risk) @ Morgan Stanley

Job Description

Job Description
Risk Analytics has an opening for a Director-level person to work on model development. The successful candidate will work extensively with credit risk models involving IRB approaches, CCAR and CECL. 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, *

Skills Required
> 4+ 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.
> 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.
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.
> Knowledge and hands-on experience in programming languages.
Desirable Skillsets
> 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.

Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximise their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing and advancing individuals based on their skills and talents.

Employement Category:

Employement Type: Full time
Industry: BFSI
Role Category: General / Other Software
Functional Area: Not Applicable
Role/Responsibilies: Director - Credit Risk Modeling (Risk)

+ View Contact

Keyskills:   big data analytics fixed income derivatives strong analytical skills environmental impact assessment credit risk analytics big data credit risk risk models data analytics risk analytics stress testing financial risk credit trading risk management risk mitigation analytical skills commercial models leveraged finance financial products hypothesis testing