Director, AI Asset Management

The Director, AI Asset Management plays a mission-critical role in shaping how our organization harnesses artificial intelligence to enhance fundamental investing decisions across our multi-asset portfolios. This leader will assist the Global Head, AI Asset Management in overseeing the strategy, governance, and performance of our proprietary AI-driven investing platform, ensuring it delivers actionable insights, robust analytics, and a sustained competitive advantage in the pursuit of long-term financial performance.

Combining deep investment acumen with technological leadership, the Director will guide cross-functional teams that bridge investment research, data science, and product development. This role demands a visionary leader who can balance innovation with operational discipline—advancing our capabilities in predictive modeling, alternative data integration, and AI-assisted investment strategies.

Position Responsibilities: 

1. Leadership & Team Management (30%)

• Lead and mentor a team of AI product managers, quantitative researchers, data scientists, and technologists focused on advancing our AI investment platform.
• Build a collaborative culture that merges data science excellence with fundamental investment insight.
• Define clear performance metrics and accountability frameworks for AI research, model delivery, and portfolio integration.
• Act as a strategic advisor to senior investment leaders on AI’s evolving role in portfolio management and research workflows.

2. Product Management & Cross-Functional Collaboration (40%)

•  Oversee the full lifecycle of the firm’s proprietary AI investing tool, from research and model development to deployment, monitoring, and enhancement.
• Partner closely with portfolio managers, analysts, and risk teams to identify high-value use cases for AI—such as company scoring models, macroeconomic signal generation, or ESG factor analysis.
• Ensure data quality, transparency, and explainability in all AI models used for investment decisions.
• Collaborate with technology, compliance, and enterprise data teams to align the AI platform with regulatory, ethical, and infrastructure standards.
• Translate business and investment objectives into technical requirements, prioritizing roadmap initiatives that maximize strategic impact.

3. Corporate Administration & Executive Leadership Support (30%)

• Serve as a strategic interface between investment leadership, technology executives, and the board—providing clear reporting on AI strategy, progress, and business outcomes.
• Lead budget planning, resource allocation, and vendor relationships related to AI infrastructure, alternative data sources, and analytics partnerships.
• Support enterprise initiatives around digital transformation, investment modernization, and responsible AI governance.
• Prepare executive briefings, thought leadership, and whitepapers on AI trends in fundamental investing and asset management.
• Oversee the full lifecycle of the firm’s proprietary AI investing tool, from research and model development to deployment, monitoring, and enhancement.
• Partner closely with portfolio managers, analysts, and risk teams to identify high-value use cases for AI—such as company scoring models, macroeconomic signal generation, or ESG factor analysis.
• Ensure data quality, transparency, and explainability in all AI models used for investment decisions.
• Collaborate with technology, compliance, and enterprise data teams to align the AI platform with regulatory, ethical, and infrastructure standards.
• Translate business and investment objectives into technical requirements, prioritizing roadmap initiatives that maximize strategic impact.

Required Qualifications: 

• Bachelor’s degree in Finance, Computer Science, Engineering, Economics, or a related field; MBA or advanced quantitative degree preferred.
• 10+ years of experience in asset management, investment technology, or analytics, with demonstrated success leading cross-functional teams and communications.

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Preferred Qualifications: 

• Demonstrated understanding of investment concepts, including some exposure to quantitative methods.
• Deep understanding of fundamental investing principles and how AI/ML can augment research, valuation, and portfolio construction processes.
• Proven expertise in product management, data governance, and product lifecycle management within a regulated financial environment.
• Exceptional leadership, communication, and stakeholder manageme