Product Manager II - Taxonomy, Financial Data

About the role

The Product Manager II - Taxonomy, Financial Data will lead the evolution of AlphaSense's structured financial data taxonomy library, ensuring both backward compatibility and future-proofing. They will collaborate with engineering, data, product, sales, and client-facing teams to align stakeholders on taxonomy decisions and translate conceptual frameworks into scalable, production-ready systems. The role requires a strong analytical mindset, expertise in data governance and taxonomy, and the ability to serve as the internal subject matter expert on data semantics.

Responsibilities

• Drive ownership of the existing financial data taxonomy library, including all client-facing labels, metric definitions, and dataset classifications.
• Set the standard for label conventions and governance principles across various data types, ensuring clients can intuitively discover, understand, and leverage the data.
• Collaborate cross-functionally with engineering, data, product, sales, and client-facing teams to align stakeholders on taxonomy decisions and translate conceptual frameworks into scalable, production-ready systems.
• Serve as the internal subject matter expert on data semantics, developing and maintaining official internal and external documentation to ensure taxonomy standards are clearly articulated and accessible to all stakeholders.
• Proactively identify gaps and inconsistencies as new datasets are onboarded, and drive resolution in a structured and scalable way.
• Design and maintain taxonomy and data structures with AI and LLM compatibility as a core consideration, ensuring labels, definitions, and conventions support model training, inference, and broader AI-driven automation.
• Lay the foundation for a future taxonomy practice by building repeatable frameworks and positioning this function for team growth over time.

Requirements

• Bachelor's degree in a highly analytical field such as Engineering, Computer Science, Business, or a related discipline.
• 5+ years of experience working with data structures, taxonomy, or data governance, with at least 2 years in a product management or closely adjacent cross-functional role.
• A genuine interest in financial data and capital markets, with an understanding of how investors and financial professionals consume, interpret, and act on data.
• A proven analytical mindset, with the ability to translate complex, ambiguous data challenges into structured frameworks and scalable solutions.
• Hands-on experience leveraging AI and LLM tools as an internal practitioner and a genuine curiosity for how consumers of financial data are integrating AI into their workflows.
• Strong organizational skills and attention to detail, with a demonstrated ability to manage multiple workstreams and competing priorities independently.
• Proficiency in data management tools such as SQL and Python, with a willingness to expand your toolkit as the role evolves.

Qualifications

• Expertise in data governance and taxonomy.
• Experience with data structures and taxonomy.
• Strong analytical and problem-solving skills.
• Ability to work collaboratively with cross-functional teams.
• Understanding of financial data and its consumption by professionals.
• Experience with AI and LLM tools.
• Organizational skills and attention to detail.
• Proficiency in data management tools.

Skills

• Data governance and taxonomy expertise.
• Data structures and taxonomy experience.
• Analytical and problem-solving skills.
• Collaboration with cross-functional teams.
• Understanding of financial data and its consumption by professionals.
• Experience with AI and LLM tools.
• Organizational skills and attention to detail.
• Proficiency in data management tools.

Benefits & Perks

• Growth opportunities in a well-funded, high-growth company.
• Autonomy to create your own schedule and do your best work.
• Flexible work arrangements, including remote work and occasional in-office days.
• Ongoing personal and professional growth through learning stipends, lunch and learns, and guest speakers.
• Regular one-on-one meetings and ongoing feedback.
• Equitable compensation and benefits package.

Pay

$128,000 - $176,000 USD

Schedule

Full-time