Morgan Stanley

Associate - Counterparty Credit Risk Analytics IMM (Risk Management)

Job Description

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 Firm’s 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.

Position Background
Risk Analytics is seeking an Associate/Director to support quantitative Counterparty Credit Risk Analytics IMM (Internal Models Method) projects and regulatory deliverables. The candidate needs to collaborate within the team and across a range of functional groups to fulfill the deliverables on a timely basis. This is a permanent role.

Primary Responsibilities include, but are not limited to:
• Research, development, enhancement, and documentation of IMM Counterparty credit risk, methodologies, and tools for regulatory and risk management purposes
• Perform analysis including model recalibrations, back-tests, stress tests, scenario, and sensitivity analyses.
• Programming of prototypes/production code (within an established C++/R /Python libraries) which will be productionized.
• Program, test and implement quantitative financial methods using Python, C++, VBA, R, Matlab and SQL
• Utilize advanced statistics, econometrics and mathematical skills including probability theory, stochastic calculus, Monte Carlo simulation, numerical analysis, optimization techniques and time series analysis
• Work with Technology on model testing, implementation, and production
• Work with risk managers and other stakeholders to address their requests for additional analysis based on specific needs as they arise
• Participate in Regulatory and validation exams by providing documentation and responses to regulators and internal validators

Skills Required
• 3-8 years of work experience in quantitative modeling, Risk Management, algorithmic trading, 
• 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.

Required Qualifications
• Graduate/Under-graduate/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.
• Candidates will have to deal in Python, SQL queries, and MS-Office on daily basis.

Desirable Skillsets
• 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 one of the following 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 maximize 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.


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