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VP - Model Risk - Predictive Modelling

Mumbai, India | Morgan Stanley

  • Industry:
    Financial Services
  • Position Type:
  • Functions:
    Risk Management
  • Experience:
    5-7 years
Job Description:
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 Morgan Stanley is seeking a Vice President to join a fast-growing team in Model Risk Management, within Firm Risk and help manage a new team responsible for the review, validation, and risk assessment of models used in Wealth Management.

 These high-visibility positions will be important strategic additions to a global team, focusing on the model risk oversight of Wealth Management models. These award-winning models use sophisticated Statistics and Machine Learning techniques.

Primary Responsibilities

 Engage in quantitative model review and risk assessment of Wealth Management models.

 Write model risk management findings in technical documents that will be presented both internally (model developers, business unit managers) as well as to regulators.

 Verbally communicate results and debate issues, concerns and methodologies with internal audiences including senior management in Firm Risk Management

 Coordinate team’s tasks and escalate issues in a timely manner.

 Perform and validation of predictive models in a variety of asset classes and product categories

 Participate in ongoing statistical/machine learning/deep learning research initiatives

 Develop computer code in R/Python/Perl or similar languages and interface with Firm’s databases to support above mentioned initiatives

 Work on Bank Model Risk projects and analyses


Skills Required:

 Possess Bachelors, Masters or Doctorate degree in a technical or quantitative-finance area

 Establish and manage a team of quantitative professionals providing independent review and risk management of Wealth Management models

 5+ years’ experience with quantitative modelling preferably in banks or large financial institution

 Expert knowledge of predictive modeling (Linear / non-Linear regression, propensity models, Statistical / Machine Learning, etc.)

 Strong programming (Python, C/C++, R etc.)

 Experience with statistical/mathematical packages (R, Matlab, Mathematica, etc.)

 Advanced problem solving

 Have experience using popular Machine Learning or Deep Learning techniques in Python.

 Have strong written and verbal communication skills; be comfortable debating issues and making formal presentations.

 Have desire to work in a dynamic, team-oriented environment focusing on concerning tasks mixing fundamental, quantitative and market-oriented knowledge and skills.

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