About the Role:
We are looking for an experienced Head of Product to lead the strategy, execution, and evolution of a next-generation financial data platform powered by AI and human expertise. This leader will own the end-to-end product vision for large-scale financial data extraction, quality, and delivery systems while building products that continuously improve through machine learning and analyst feedback.
This is a highly strategic leadership role requiring deep expertise in data products, AI-assisted workflows, platform thinking, and cross-functional execution. You will partner closely with Engineering, AI/ML, Data Operations, and Quality teams to build products that deliver highly accurate, scalable financial intelligence.
Key Responsibilities
Product Strategy & Ownership
- Own the end-to-end product roadmap for the financial data platform, covering document acquisition, automated extraction, taggidang, analyst workflows, quality, and data delivery.
- Define and execute the long-term product vision aligned with business priorities and customer needs.
- Prioritize initiatives across multiple product areas while balancing customer impact, technical feasibility, and operational efficiency.
- Drive roadmap planning across a multi-year horizon, including expansion into new financial datasets and intelligence products.
Platform & Workflow Innovation
- Design and build scalable internal platforms that enable analysts to efficiently manage the complete lifecycle of financial data.
- Simplify fragmented operational workflows into unified product experiences.
- Build products that seamlessly integrate AI automation with human review to continuously improve model accuracy and productivity.
- Optimize systems to improve data coverage, processing speed, and accuracy simultaneously.
AI & Data Products
- Partner with AI and Engineering teams to develop AI-assisted financial data extraction capabilities.
- Drive the evolution of ML-powered workflows through analyst feedback loops and continuous model improvement.
- Evaluate AI/ML architectures and contribute to technical product decisions around data processing, retrieval, validation, and quality.
- Define future product capabilities across structured financial datasets, earnings information, transcripts, consensus estimates, and alternative data sources.
Quality & Operational Excellence
- Establish and scale a company-wide product quality framework.
- Define quality standards, testing methodologies, severity classifications, and operational governance.
- Build mechanisms to capture production feedback and convert insights into product improvements.
- Create measurable quality KPIs that become core operational metrics.
Leadership & Organization Building
- Lead and mentor Product Managers across multiple product domains.
- Build and scale cross-functional teams across Product, Engineering, and Quality.
- Drive hiring and organizational growth while fostering a high-performance product culture.
- Make prioritization and resource allocation decisions across competing business initiatives.
Cross-functional Leadership
- Collaborate closely with Engineering, AI/ML, Data Science, Operations, and Business stakeholders.
- Drive execution across multiple teams while maintaining alignment on strategic objectives.
- Make high-impact product decisions with speed, clarity, and accountability.
What We're Looking For
Experience
- 8–12+ years of Product Management experience building and scaling complex data or platform products.
- Proven experience leading large cross-functional teams in high-growth technology organizations.
- Experience managing Product organizations while partnering closely with Engineering and Operations.
- Demonstrated success owning products from strategy through execution and scale.
Product Expertise
- Strong background in data platforms, content platforms, search, or financial data products.
- Experience building AI-assisted or human-in-the-loop workflows.
- Experience designing internal operational tools, analyst platforms, or workflow management systems.
- Track record of building products that improve through user feedback and operational learning.
Technical Acumen
- Strong understanding of AI/ML product development and modern data architectures.
- Ability to review technical designs and engage in architectural discussions with Engineering teams.
- Familiarity with ML pipelines, LLM-based systems, data extraction, retrieval, validation, and automation workflows.
- Comfortable balancing technical trade-offs with business priorities.
Quality & Data Excellence
- Experience building quality programs in data-intensive or accuracy-critical environments.
- Ability to define quality metrics, testing strategies, governance frameworks, and continuous improvement processes.
- Strong analytical mindset with experience defining product KPIs and operational metrics.
