Executive Director Jobs

About The Position

Requirements

• Approximately 8-10 years of relevant experience building, using, or validating models in asset management, investment management, wealth management, advisory platforms, portfolio analytics, or related quantitative roles; prior second-line model validation experience is preferred.
• Strong experience with portfolio and fund construction, portfolio risk management, asset allocation, capital market assumptions, goal-based or retirement planning, investment risk analytics, and advisory tools.
• Experience with portfolio optimization and Monte Carlo simulation frameworks, including applications to constrained optimization, tracking error, risk budgeting, wealth projections, scenario analysis, downside risk, and probability-of-success metrics.
• Experience with factor models, asset class assumptions, covariance estimation, expected return assumptions, benchmark construction, portfolio constraints, model performance monitoring, and key asset management business risks.
• Experience engaging with vendors or third-party model providers, including obtaining methodology documentation, challenging proprietary approaches, assessing limitations, evaluating model performance and controls, and working with platforms such as BlackRock Aladdin, MSCI Barra, or similar tools.
• Master's or Doctorate degree, or equivalent experience, in Finance, Business Administration, Economics, Mathematics, Statistics, Computer Science, Engineering, Operations Research, Financial Engineering, or a related quantitative or technical business field.
• Ability to independently assess model conceptual soundness, implementation quality, data lineage, controls, monitoring, and use-case appropriateness, with a risk management-oriented mindset and willingness to speak up constructively.
• Strong written, verbal, and interpersonal communication skills, including comfort leading meetings, making formal presentations, producing committee materials, briefing senior stakeholders, and building credibility across investment, quantitative, technology, product, vendor, control, audit, and regional teams.

Nice To Haves

• Hands-on experience with quantitative programming and data analysis tools such as Python, R, MATLAB, SQL, or comparable languages is preferred; experience with GenAI agents or AI-enabled workflow tools is desirable; CFA, FRM, ML, or related quantitative or technology certifications are a plus.

Responsibilities

• Lead a small global team executing independent reviews of Wealth Management and Investment Management models and tools, with accountability for execution quality, prioritization, peer review, stakeholder engagement, and clear validation conclusions.
• Provide credible challenge on model design and business use across portfolio and fund construction, portfolio risk management, optimization, Monte Carlo simulation, factor-based analytics, asset allocation, retirement planning, and client outcome metrics.
• Engage with model owners, developers, product teams, investment teams, technology partners, control functions, and third-party vendors to understand model design, testing evidence, limitations, risk mitigants, performance information, and platform controls.
• Oversee review and challenge of vendor-provided methodologies and outputs, including factor risk models, optimization engines, scenario analytics, portfolio risk decomposition, stress testing, performance attribution tools, and related platform capabilities.
• Guide identification, communication, and resolution of model risk issues, ensuring validation reports clearly articulate key risks, conclusions, remediation expectations, compensating controls, and business implications.
• Synthesize thematic and idiosyncratic model risk observations across the validation portfolio, including recurring risks related to model limitations, data quality, monitoring, vendor dependencies, platform integration, scenario design, and business-use alignment.
• Support new products, new business initiatives, model changes, platform enhancements, expanded model use cases, and emerging model types, including AI/ML models, GenAI-enabled tools, and agentic workflows.

Benefits

• Morgan Stanley sponsored benefit programs