# Data Product Manager Remote from[USA](https://jobicy.com/job-region/usa.md)Annual salary Undisclosed Salary information is not provided for this position. Check our [Salary Directory](https://jobicy.com/salaries.md) to estimate the average compensation for similar roles.Department [Product & Operations](https://jobicy.com/categories/management.md) Employment type Full Time, Job posted13 Jun 2026Apply before13 Jul 2026Experience level Senior Views / Applies 1769 / 93 [About company](https://jobicy.com/company/yipitdata.md) * Share About [YipitData](https://jobicy.com/company/yipitdata.md) YipitData provides reliable insights to investment funds and corporations by analyzing billions of data points. [Market Research](https://jobicy.com/company-category/market-research.md) * 2013 Actively Hiring Verified job posting This job post has been [manually reviewed](https://jobicy.com/tools/help-center/employee/how-does-jobicy-verify-the-legitimacy-of-remote-job-listings.md) for authenticity and compliance. ### AI Summary YipitData is seeking a Data Product Manager to lead the development of an AI-powered product that transforms how clients interact with alternative data. The role involves owning the translation of raw datasets into scalable, AI-ready data products, designing methodologies, and defining how the product uses data to deliver reliable insights. The ideal candidate has 3-6 years of experience in data product management, strong SQL skills, and thrives in ambiguity. This position is remote-friendly and based in New York, NY. ### Role DNA Job Complexity Easy Hard Pace & Pressure Relaxed Fast-paced Autonomy Level Guided Full Ownership Communication Load Independent Highly Collaborative AI Insight The role requires deep analytical rigor, designing methodologies from scratch, and working with complex alternative datasets, which makes it challenging but not the hardest level. ### Salary Analysis Median Market Rate $150,000US Market $110k – 200k 0 $220k AI Insight The offered salary is not specified, but based on the US market for a Data Product Manager with 3-6 years of experience, the median is around $150,000. The role is in New York with remote flexibility, which may adjust the compensation. ### Core Skills Required [Data Product Management](https://jobicy.com/jobs?search_keywords=Data+Product+Management.md) [SQL](https://jobicy.com/jobs?search_keywords=SQL.md) [Methodology Design](https://jobicy.com/jobs?search_keywords=Methodology+Design.md) [AI/ML](https://jobicy.com/jobs?search_keywords=AIML.md) [Alternative Data](https://jobicy.com/jobs?search_keywords=Alternative+Data.md) [Data Engineering](https://jobicy.com/jobs?search_keywords=Data+Engineering.md) [Product Strategy](https://jobicy.com/jobs?search_keywords=Product+Strategy.md) [Cross-functional Collaboration](https://jobicy.com/jobs?search_keywords=Crossfunctional+Collaboration.md) [Data Quality](https://jobicy.com/jobs?search_keywords=Data+Quality.md) [Analytics Engineering](https://jobicy.com/jobs?search_keywords=Analytics+Engineering.md) ### Cover Letter Sample Dear Hiring Manager, I am excited to apply for the Data Product Manager role at YipitData. With a strong background in data product management and analytics engineering, I have successfully translated complex alternative datasets into scalable, AI-ready products that deliver actionable insights. My experience includes designing methodologies, managing data pipelines, and collaborating cross-functionally to drive product strategy. At my previous role, I owned the end-to-end data product lifecycle, from source evaluation to production deployment, ensuring data quality and methodological soundness. I am particularly drawn to YipitData's ambitious AI-powered vision and would love to contribute to shaping how clients interact with data. Thank you for considering my application. I look forward to the opportunity to discuss how my skills align with your needs. Copy ### Sample Interview Questions How do you approach designing a methodology to normalize disparate datasets for a specific business question?I start by understanding the business question and the key metrics needed. Then I assess each dataset's strengths, biases, and coverage. I design a normalization process that aligns data schemas, handles missing values, and ensures consistency through transformation rules. I validate the methodology with sample data and iterate based on feedback.Describe a time you had to deal with a data quality issue in a product. How did you handle it?At a previous job, we discovered a pipeline bug causing incorrect aggregations. I immediately notified stakeholders, rolled back the data, and initiated an incident management process. I worked with engineering to fix the bug, added validation checks, and documented the incident to prevent recurrence.How do you decide which datasets to prioritize for a new AI feature?I evaluate datasets based on customer value, signal quality, scalability, and methodological feasibility. I prioritize datasets that answer high-impact questions and are reliable. I also consider the cost and effort to onboard and maintain the data.Explain how you would ensure an AI-powered product does not over-interpret data. What guardrails would you set?I would define clear query patterns and failure modes for the product. Implementing confidence scores and uncertainty intervals for outputs. Guardrails include limiting extrapolation beyond data ranges, requiring human review for certain decisions, and testing with edge cases.How do you collaborate with data engineering to shape data pipelines?I work closely with data engineers to define data requirements, schema designs, and quality checks. I provide clear documentation and source context. We have regular syncs to align on priorities and address pipeline dependencies. Product · New York, NY (Remote-Friendly) ## About the Role YipitData is making one of its most ambitious Product bets: building an AI-powered product that transforms how clients interact with data. This initiative sits at the center of our product strategy and represents a fundamentally new way for customers to access and derive value from our data. As a Data Product Manager, you will play a pivotal role in making that vision a reality. You will own the path from raw alternative data to trusted, product ready intelligence—determining how complex datasets are structured, interpreted, and ultimately surfaced to customers. This role sits at the intersection of data, product, and AI. You will work with diverse alternative datasets and develop the methodologies that transform those signals into reliable business insights. You will also serve as a key authority on how the product uses data, helping define what conclusions are methodologically sound, what questions can be answered confidently, and where appropriate guardrails should exist. Success in this role requires both analytical rigor and a builder’s mindset. You’ll thrive in ambiguity, tackle problems without established playbooks, and help shape the future of one of YipitData’s most strategic products. Your work will directly influence how hundreds of customers interact with our data and how this product scales over time. ## What You’ll Do Data Source Ownership & Methodology Design * Own the translation of raw alternative datasets into scalable, AIready data products. * Design methodologies that answer high-value business questions, determining how disparate datasets should be combined, normalized, and interpreted. * Partner closely with Data Engineering to shape source data pipelines into clean, well-structured datasets with clear definitions and documentation. * Develop deep expertise in the strengths, limitations, biases, and coverage characteristics of key datasets and ensure those nuances are reflected in downstream outputs. ## AI Product Intelligence & Knowledge Systems * Define how the product should use 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 delivers accurate and explainable answers. * Establish standards for how the product reasons across multiple datasets, preventing over-interpretation and ensuring conclusions remain statistically defensible. * Serve as the final reviewer for methodology-related changes that impact product behavior. Product Development & Customer Problem Solving * Translate customer questions into scalable methodologies, data models, and product capabilities. * Expand the range of questions the product can answer 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 increase the commercial value of the AI product. * Help shape the product roadmap by turning emerging customer needs and experimental insights into repeatable product functionality. Data Quality & Operational Excellence * Coordinate testing and validation of staged data changes before they reach production. * Own incident management processes for data quality issues, methodology changes, and upstream source disruptions. * Build and maintain a library of quality checks tailored to the unique requirements of AI-powered customer experiences. * Ensure the product consistently surfaces reliable, accurate, and internally consistent information across all supported 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 fluency in SQL; comfort with data pipelines, schema changes, and upstream/downstream data dependencies. * Experience owning data documentation, metric definitions, or data quality programs—not just conducting ad hoc analysis. * A track record of cross-functional coordination, ideally between technical data teams and product or commercial stakeholders. * Strong project management instincts: you can run a triage process, maintain a quality library, and coordinate across multiple stakeholder groups without dropping balls. * Clear, structured communication—you can translate complex data methodology questions into guidance that non-technical stakeholders can act on. * A demonstrable track record of building—shipping things, solving hard problems, and leaving a clear mark on the products you’ve worked on. * An entrepreneurial mindset: you’re comfortable with ambiguity, energized by new problem spaces, and don’t need a fully paved road to make progress. * Deep experience with alternative data, panel data, or similarly complex, nuanced data sources is required—you need to understand the quirks, limitations, and methodological subtleties of these datasets and be able to encode that understanding for an AI driven product. * Prior experience in or exposure to AI/ML products, LLM-based agents, or evaluation frameworks is a strong plus. ## What We Offer * Competitive base salary with comprehensive benefits * Fully remote-friendly within the United States * Flexible work hours and flexible vacation * Generous 401(k) match, parental leave, wellness budget, and learning reimbursement * A growth-oriented environment where advancement is driven by impact—not tenure Please note: for this position, we are not able to consider candidates who currently or in the future will require visa sponsorship. YipitData is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity employer. Show more [Apply now >](https://jobicy.com/jobs/146439-data-product-manager.md) > Annual salary information is not provided for this position. 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