Product Manager II, Financial Data

Summary

AlphaSense is a market intelligence platform that uses AI-driven search and trusted public and private content to help professionals make informed decisions. The Product Manager II will specialize in financial data generation and presentation, owning the financial data taxonomy, defining data-generation rules and requirements, and collaborating with technical and business stakeholders to build accurate, scalable, and AI-compatible datasets.

Responsibilities

• Own and evolve AlphaSense's proprietary financial data taxonomy, inclusive of financial metrics reported across sectors, accounting standards, statements, and reporting patterns, ensuring both backwards compatibility and future proofing
• Understand financial data consumption patterns of capital markets participants and define how data generation rules apply across all sectors and data types, ensuring clients can intuitively discover, understand, and leverage the data AlphaSense has to offer
• Serve as the internal subject matter expert on financial data generation and presentation, and develop and maintain official internal and external documentation ensuring data standards are clearly articulated and accessible to all stakeholders
• Collaborate cross-functionally with engineering, research, product, sales, and client-facing teams to align stakeholders on financial data generation and presentation rules and translate them into a dataset with depth, accuracy, and relevance to clients
• Proactively identify gaps and inconsistencies as new companies, metrics, and datasets are onboarded, driving efficient resolution in coordination with relevant stakeholders
• Define the use cases and requirements for new financial datasets that extend beyond the three core financial statements, driving their onboarding in a structured and scalable way
• Design and maintain financial data structures and taxonomy 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 financial data expansion through building repeatable frameworks and processes, while positioning the dataset for scalable accuracy, relevance, and growth

Skills

• 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

Must Haves

• 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

Benefits

• Growth opportunities in a well-funded, high-growth company that’s aiming to be the new fundamental dataset of record.
• Autonomy to create your own schedule and do your best work.
• This team primarily works remotely and also has an office located in New York City for optional in-office days.
• A learning stipend, lunch and learns, and guest speakers.
• Ongoing feedback, career development, and weekly 1-on-1s.
• All the equipment you need to work remotely and effectively.
• A performance-based bonus.
• Equity.