Principal Product Manager, Data

About the Company

Gemini is a global crypto and Web3 platform founded by Cameron and Tyler Winklevoss in 2014, offering a wide range of simple, reliable, and secure crypto products and services to individuals and institutions in over 70 countries. Our mission is to unlock the next era of financial, creative, and personal freedom by providing trusted access to the decentralized future. We envision a world where crypto reshapes the global financial system, internet, and money to create greater choice, independence, and opportunity for all — bridging traditional finance with the emerging cryptoeconomy in a way that is more open, fair, and secure.

As a publicly traded company, Gemini is poised to accelerate this vision with greater scale, reach, and impact.

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.

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.

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

• 10+ years of experience in product management, program management, or equivalent roles, with at least 5+ years focused on data, ML, or analytics
• Proven track record of shipping data products (e.g., ML‑driven features, self‑service analytics platforms, reporting suites, or governance tools)
• Strong understanding of data and ML life cycles — from ingestion,…