Principal Product Manager, Data

At Gemini, our Data team is the engine that powers insight, innovation, and trust across the company. We bring together world-class data engineers, platform engineers, machine learning engineers, analytics engineers, and data scientists — all working in harmony to transform raw information into secure, reliable, and actionable intelligence. From building scalable pipelines and platforms, to enabling cutting-edge machine learning, to ensuring governance and cost efficiency, we deliver the foundation for smarter decisions and breakthrough products. We thrive at the intersection of crypto, technology, and finance, and we’re united by a shared mission: to unlock the full potential of Gemini’s data to drive growth, efficiency, and customer impact.

The Role:

Gemini’s data organization spans multiple disciplines — data engineering, platform engineering, machine learning engineering, data science, and analytics engineering. These teams power our ability to operate securely, comply with regulation, generate insights, build machine learning–driven products, and deliver reliable reporting.

As a Principal Data Product Manager, you will own the strategy, prioritization, and delivery of data-centric initiatives across the company. You will identify and champion innovative ways to leverage our data assets — whether through new analytics products, ML-powered features, or improved governance and self-service. You will serve as the connective tissue between data teams and cross-functional stakeholders (product, engineering, finance, compliance, operations, security), ensuring we’re building the right data products at the right time, and with measurable business impact.

This is a highly visible, senior IC role where you’ll drive product vision for data, set roadmap, and influence leadership and execution across the org.

This role is required to be in person twice a week at either our New York City, NY or San Francisco, CA office. 

Responsibilities:

1. Define and drive our data product strategy, aligning opportunities ot more effectively leverage our data with the company’s objectives
2. Translate business challenges into data-driven solutions: data products, ML models, dashboards, or infrastructure investments
3. Own and maintain the data product roadmap, prioritizing initiatives across multiple stakeholders while balancing short term vs long term business needs
4. Identify and manage trade-offs between data staffing capacity, cross-team dependencies, and business priorities
5. Act as program driver across diverse data roles: staff data engineers, data platform engineers, ML engineers, ML platform engineers, analytics engineers, and data scientists
6. Lead cross-functional project management for data initiatives, ensuring milestones are met, blockers are cleared, and scope is aligned
7. Partner with executive stakeholders to identify opportunities, gather requirements, and report on KPIs for data products
8. Evangelize data best practices and the value of data-driven decision-making across the org

Minimum Qualifications:

1. 10+ years of experience in product management, program management, or equivalent roles, with at least 5+ years focused on data, ML, or analytics
2. Proven track record of shipping data products (e.g., ML-driven features, self-service analytics platforms, reporting suites, or governance tools)
3. Strong understanding of data and ML lifecycles — from ingestion, modeling, and governance to feature engineering, model training, and deployment
4. Hands-on experience partnering with data engineers, ML engineers, and data scientists
5. Ability to translate complex data and ML concepts into business value for non-technical stakeholders
6. Exceptional skills in roadmap development, prioritization, and cross-functional coordination
7. Strong written and verbal communication skills; comfort presenting to executive leadership
8. Experience in fintech, crypto, or regulated industries a plus

Preferred Qualifications:

1. Domain expertise in crypto / blockchain / Web3 data (on-chain data, DeFi protocols, transaction analytics)
2. Experience with ML platforms (feature stores, model registries, inference hosting) or data platforms (lakehouse, governance, catalogs)
3. Familiarity with compliance and regulatory constraints on data (AML, KYC, GDPR, SOX, SOC2)
4. Background in analytics, statistics, or data science — able to independently explore and validate data-driven opportunities

Salary Range: The base salary range for this role is between $192,500 - $275,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.