Head of Portfolio Risk & Analytics

Brown Brothers Harriman•New York, NY

About The Position

At BBH, Partnership is more than a form of ownership—it’s our approach to business and relationships. We know that supporting your professional and personal goals is the best way to help our clients and advance our business. We take that responsibility seriously. With a 200-year legacy and a shared passion for what’s next, this is the right place to build a fulfilling career. The Investment Research Group (IRG) Head of Portfolio Risk & Analytics will lead the development and application of quantitative frameworks that support portfolio construction, risk management, and investment research across the Wealth Management platform. This individual will oversee the design and implementation of robust analytical tools, leveraging market data, portfolio modeling, and advanced statistical techniques to enhance investment decision-making. This role sits at the intersection of investment strategy, data science, and technology, and will partner closely with the CIO, Deputy CIO, Head of Investment Research, Head of Investment and Portfolio Strategy, and research analysts to deliver scalable, insight-driven solutions.

Requirements

Advanced degree in a quantitative discipline (e.g., MS or PhD in Computational Finance, Financial Engineering, Statistics, Mathematics, or a related field) preferred
8–12+ years of experience in quantitative research, portfolio construction, or risk management within asset or wealth management
Deep understanding of portfolio theory, factor models, and risk analytics
Proficiency with market data and analytics platforms, such as Bloomberg Terminal and FactSet, including data extraction, analysis and integration into quantitative workflows
Strong programming skills (e.g., Python, R, MATLAB)
Experience with portfolio optimization, back-testing frameworks, and large datasets
Strong analytical and problem-solving capabilities with attention to detail
Ability to translate complex quantitative concepts into actionable investment solutions
Excellent communication skills, with the ability to engage both technical and non-technical stakeholders
Collaborative mindset with a focus on innovation and continuous improvement

Nice To Haves

Familiarity with private markets, commitment pacing, and liquidity modeling strongly preferred
Experience with direct indexing, tax-aware investing, and customization strategies is highly desirable

Responsibilities

Lead the development and oversight of quantitative risk frameworks for model portfolios, including factor exposures, scenario analysis, and stress testing
Enhance portfolio construction methodologies using optimization techniques and risk-adjusted return frameworks
Monitor and evaluate portfolio characteristics, ensuring alignment with investment objectives and risk tolerances
Liaison with the broader CP Investment Portfolio Risk Management team
Develop pacing frameworks and optimization models for private market allocations, including commitment pacing, liquidity forecasting, and vintage diversification
Design, implement, and continuously improve portfolio analytics and reporting tools
Oversee ongoing monitoring of portfolios, including performance attribution, factor analysis, and risk decomposition
Partner with performance teams to enhance model portfolio and client reporting, improving accuracy, transparency, and insight delivery
Develop proprietary performance/risk/exposure dashboards and reports to communicate insights to investment teams and stakeholders
Develop proprietary applications that the front office (RMs) can use to inform portfolio composition, sizing, and positioning
Develop scalable frameworks for quantitative analytics for custom client portfolios
Build and maintain quantitative screening tools for equities and ETFs, incorporating fundamental, technical, and factor-based signals
Support investment idea generation through data-driven research and back-testing of strategies and portfolios
Conduct quantitative analysis to help inform capital market assumptions, including expected returns, volatility, and correlations across asset classes
Collaborate on asset allocation to integrate quantitative insights into portfolio construction
Oversee the automation of portfolio data workflows, analytics, and charting processes
Partner with technology teams to enhance data infrastructure, ensuring accuracy, scalability, and efficiency
Implement best practices in data management and reproducible research