Director, Product Management

Overview

As head of Stewardship Intelligence, you will define the vision and roadmap for a key data product that powers governance, proxy voting, and compensation insights for institutional clients. You will lead both Product Management and Research, directing cross-functional teams to deliver trusted, scalable data experiences and AI-enabled improvements. You will translate market needs into priorities, ensure data quality and timeliness, and partner across Engineering, UX, Commercial, and Marketing to drive adoption and value. This is a domain-driven leadership role with a strong impact on how investors and issuers access governance intelligence.

Pay / Benefits

• flexible work environment
• health benefits
• generous time off policy
• wellness programs
• hybrid work model

Responsibilities

• Own and refine the product vision, strategy, and prioritisation for Stewardship Intelligence across meeting, compensation, governance, and proxy-voting data
• Lead and organize Product Management and Research teams with emphasis on AI-enabled ways of working
• Improve dataset coverage, methodology, quality, traceability, and timeliness using process redesign, automation, and AI
• Partner with Engineering and UX to build high-quality data service experiences
• Develop deep understanding of institutional clients and use customer and market insights to guide decisions
• Collaborate with Commercial, Marketing, Sales and Customer Success to support positioning, launch readiness, adoption and ongoing value

Key requirements

• Significant experience in Product Management, Research Operations, Data Products or related disciplines with leadership of complex products or datasets
• Mandatory domain experience in stewardship, proxy voting, corporate governance, executive compensation, investor relations or related capital-markets domain
• Proven track record delivering B2B SaaS, data or intelligence products from discovery to roadmap execution and ongoing improvement
• Proven leadership of research or data operations teams handling large-scale structured datasets and enterprise-grade quality

• Exceptional communication
• Analytical judgement
• Stakeholder management
• AI integration
• Data-as-a-Service
• Automation and process redesign

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