Associate - Data Science and Surveillance Model Review

Key Skills

Microsoft-Excel, Java Programming, Python Programming, SQL, R Programming, Powerpoint

Job Description

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, operational, model and other risks.

Background on the Position

This role will reside within Firm Risk Management's Model Risk Management team responsible for the Firm's management of risks related to the implementation and use of models, covering all aspects of the Firm?s businesses and implementing key regulatory requirements. This position requires strong technical, leadership, and organizational skills.

Primary Responsibilities

• Perform independent review and validation of Data Science and rules based models in Fraud/Operations, Technology, Cybersecurity and Legal and Compliance.
• Conduct model review activities compliant with Model Risk Management policies and procedures, regulatory guidance, and industry leading practices, including evaluating/challenging conceptual soundness, quality of modeling methodology, testing, model limitations, and on-going monitoring
• Write comprehensive validation documentation for models that satisfies the Firm?s internal model approval functions, audit requirements, and regulatory standards and communicate validation conclusion to managers and stakeholders
• Represent Model Risk Management team in interactions with internal audit and regulatory agencies as required
• Keep up to date with trends in economic sanctions policies, financial markets, fiscal and financial policies and re-assess adequacy and relevance of model development and validation activities

QUALIFICATIONS

Experience

• Masters or Doctorate degree in a technical area such as Mathematics, Statistics, Data Science, Physics or related fields
• Familiarity with essential quantitative techniques (e.g.: Hyperparameter Optimization) used in Data Science models and rules-based model techniques (e.g.: BTL/ATL)
• Experience using any programming language (e.g. Python, R, etc.), SQL and Microsoft Office (Excel, PowerPoint, Word)
• Strong written and verbal communication skills. Must be comfortable leading meetings and making formal presentations
• Self-starter, highly organized and able to work in a diverse and dynamic team, managing challenging tasks and leveraging quantitative and market-oriented knowledge and skills
• Desire to work in a dynamic, team-oriented environment focusing on challenging tasks mixing fundamental, quantitative and market-oriented knowledge and skills
• Familiar with regulatory requirements (e.g. CCAR, SR 11-7) and regulators (Fed, OCC, PRA, EBA)
• Familiarity with tree-based models and statistical models
• Previous experience in risk management or model development/validation roles a plus