Data Product Manager

About the Role

YipitData is making a significant investment in an AI-powered product designed to revolutionize client interaction with data. This initiative is central to our product strategy, offering a fundamentally new way for customers to access and derive value from our information.

As a Data Product Manager, you will be instrumental in bringing this vision to life. Your responsibility will be to guide the transformation of raw alternative data into trusted, product-ready intelligence, defining how complex datasets are structured, interpreted, and presented to clients.

This position is at the nexus of data, product, and AI. You will work with a variety of alternative datasets, developing methodologies to convert these signals into reliable business insights. You will also be a key authority on the product's data utilization, helping to define methodological soundness, the scope of answerable questions, and necessary guardrails.

Success requires both analytical depth and a proactive, hands-on approach. You'll excel in ambiguous environments, tackle challenges without pre-existing frameworks, and help shape the evolution of a strategically vital YipitData product. Your contributions will directly influence customer engagement with our data and the scalability of this product.

What You'll Do

Data Source Ownership & Methodology Design

• Own the process of converting raw alternative datasets into scalable, AI-ready data products.
• Design methodologies to address high-value business questions, determining how to combine, normalize, and interpret diverse datasets.
• Collaborate closely with Data Engineering to refine source data pipelines, ensuring clean, well-structured datasets with clear definitions and documentation.
• Develop deep expertise in the strengths, limitations, biases, and coverage of key datasets, ensuring these nuances inform downstream outputs.

AI Product Intelligence & Knowledge Systems

• Define how the product leverages different datasets, including valid query patterns, edge cases, failure modes, and methodological guardrails.
• Own metric definitions, data lineage, and documentation to ensure the product consistently provides accurate and explainable results.
• Establish standards for how the product reasons across multiple datasets, preventing over-interpretation and ensuring statistically defensible conclusions.
• Act as the final reviewer for methodology-related changes that affect product behavior.

Product Development & Customer Problem Solving

• Translate customer inquiries into scalable methodologies, data models, and product capabilities.
• Expand the product's scope by enabling new forms of segmentation, cohort analysis, behavioral measurement, and cross-dataset insights.
• Partner with Product, Engineering, and Leadership to identify new data sources, use cases, and capabilities that enhance the AI product's commercial value.
• Contribute to the product roadmap by transforming emerging customer needs and experimental findings into repeatable product functionality.

Data Quality & Operational Excellence

• Coordinate testing and validation of staged data changes prior to production release.
• Manage incident response for data quality issues, methodology changes, and upstream source disruptions.
• Develop and maintain a library of quality checks specifically designed for AI-powered customer experiences.
• Ensure the product consistently delivers reliable, accurate, and internally consistent information across all use cases.

You Are Likely to Succeed If You Have

• 3–6 years of experience in data product management, product analytics, analytics engineering, data science, market intelligence, alternative data, or a closely related field.
• Strong proficiency in SQL; comfortable with data pipelines, schema modifications, and understanding upstream/downstream data dependencies.
• Experience owning data documentation, metric definitions, or data quality programs, beyond ad hoc analysis.
• A proven ability to coordinate cross-functionally, particularly between technical data teams and product or commercial stakeholders.
• Strong project management skills: adept at managing triage processes, maintaining quality libraries, and coordinating multiple stakeholder groups effectively.
• Clear, structured communication abilities: capable of translating complex data methodology questions into actionable guidance for non-technical stakeholders.
• A demonstrable track record of building and shipping products, solving challenging problems, and leaving a significant impact on the products you've worked on.
• An entrepreneurial mindset: comfortable with ambiguity, motivated by new problem spaces, and able to make progress without established roadmaps.
• Deep experience with alternative data, panel data, or similarly complex, nuanced data sources is essential. You must understand the intricacies, limitations, and methodological subtleties of these datasets and be able to translate this understanding for an AI-driven product.
• Prior experience with AI/ML products, LLM-based agents, or evaluation frameworks is a significant advantage.

What We Offer

• Competitive base salary with comprehensive benefits.
• Fully remote work environment within the United States.
• Flexible work hours and vacation policy.
• Generous 401(k) match, parental leave, wellness budget, and learning reimbursement.
• A growth-focused environment where advancement is based on impact, not tenure.