Product Manager

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. What You’ll Do: 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 Who You Are : 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