Product Manager II - Taxonomy, Financial Data

The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content.

The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us!

Alpha-Sense is the leading market intelligence platform for key decision makers. We power some of the world’s most well-respected institutional investors, corporations, and consultancies through the largest and most comprehensive database of primary and market information. Our products and services enable clients to discover unmatched insights and answers to the most challenging questions they face to help them make better informed decisions.

Join the Financial Data Team at Alpha-Sense as a Product Manager specializing in Taxonomy. Successful candidates will bring a strong analytical mindset, expertise in data governance and taxonomy, and the ability to drive alignment across technical and business stakeholders.

• →Drive ownership - Own and evolve the existing structured financial data taxonomy library at AlphaSense, inclusive of all client-facing labels, metric definitions and dataset classifications, ensuring both backwards compatibility and future proofing.
• →Set the standard - Understand existing naming standards and define how label conventions and governance principles apply across a growing range of data types, ensuring clients can intuitively discover, understand, and leverage the data Alpha-Sense has to offer.
• →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, and develop and maintain official internal and external documentation ensuring 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 — building repeatable frameworks and positioning this function for team growth over time

• 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