Staff Data Scientist

At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs. If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value. THE WORK: We're looking for a Staff Data Scientist to be the technical lead across Ripple's diverse product and business portfolio. You'll define the analytics vision, build the scientific frameworks the org uses to evaluate product and business performance, and use AI tooling to accelerate the speed and reach of analytics across the company. In this role, you'll partner with product and business leads to frame the most important questions, set the analytical bar, and ensure decisions across surfaces rest on a consistent, thorough foundation. You'll operate as a force multiplier -- solving the hardest problems, building the frameworks others reuse, and levelling up data scientists across teams. WHAT YOU’LL DO: - Be the DS tech lead across multiple product and business teams: setting methodological standards and unblocking the hardest analytical problems across areas including Treasury, Markets, Custody, and XRPL. - Partner with product and business leads to define analytics strategy: shaping which initiatives to invest in, what success looks like, and how we'll know. - Build the scientific frameworks Ripple reuses at scale: product and network health metrics, causal inference playbooks, liquidity and adoption models, and forecasting approaches that work across institutional and developer surfaces. - Pioneer AI-accelerated analytics: applying LLMs and agentic workflows to scale insight generation, automate routine analysis, and enable self-serve exploration for non-DS partners. - Drive evidence-based evaluation of growth across customers, corridors, and on-chain activity, surfacing the causal drivers behind adoption and volume. - Define and communicate the metrics leadership runs on: translating complex results into clear narratives for Ripple executives and external stakeholders. - Raise the bar for the DS function through thought leadership and mentorship across embedded teams. WHAT YOU'LL BRING: - 8+ years in data science or quantitative analysis, with a track record of senior level impact across multiple teams. - Demonstrated technical leadership across cross-functional teams, influencing roadmaps and strategy at both executive and execution levels. - Proven experience designing reusable analytics and measurement frameworks that scale across products. - Hands-on experience applying AI to accelerate analytics workflows (agentic analysis, AI-assisted insight generation, natural-language data interfaces). - Deep expertise in experimentation, causal inference, forecasting, and statistical modeling in a product environment. - Expertise in Python or R, fluency in SQL, and experience with large-scale data tech (Databricks, Airflow, dBT a plus). - Experience with FinTech, payments, crypto, or blockchain data is a strong plus. - Advanced degree (MS, PhD) in a quantitative field preferred. - Exceptional communication skills — able to turn technical depth into executive-ready narratives. WHO WE ARE: Do Your Best Work - The opportunity to build in a fast-paced start-up environment with experienced industry leaders - A learning environment where you can dive deep into the latest technologies and make an impact. A professional development budget to support other modes of learning. - Thrive in an environment where no matter what race, ethnicity, gender, origin, or culture they identify with, every employee is a respected, valued, and empowered part of the team. - In-office collaboration for moments that matter is important to our culture, and we give managers and teams the flexibility to decide which 10+ days a month they come in. - Bi-weekly all-company meeting - business updates and ask me anything style discussion with our Leadership Team - We come together for moments that matter which include team offsites, team bonding activities, happy hours and more! Take Control of Your Finances - Competitive salary, bonuses, and equity - Competitive benefits that cover physical and mental healthcare, retirement, family forming, and family support - Employee giving match - Mobile phone stipend Take Care of Yourself - R&R days so you can rest and recharge - Generous wellness reimbursement and weekly onsite & virtual programming - Generous vacation policy - work with your manager to take time off when you need it - Industry-leading parental leave policie

8+ years in data science or quantitative analysis with a track record of senior level impact across multiple teams. Demonstrated technical leadership across cross-functional teams, influencing roadmaps and strategy at both executive and execution levels. Proven experience designing reusable analytics and measurement frameworks that scale across products. Hands-on experience applying AI to accelerate analytics workflows (agentic analysis, AI-assisted insight generation, natural-language data interfaces). Deep expertise in experimentation, causal inference, forecasting, and statistical modeling in a product environment. Expertise in Python or R, fluency in SQL, and experience with large-scale data tech (Databricks, Airflow, dBT a plus). Experience with FinTech, payments, crypto, or blockchain data is a strong plus. Advanced degree (MS, PhD) in a quantitative field preferred. Exceptional communication skills — able to turn technical depth into executive-ready narratives.

Be the DS tech lead across multiple product and business teams: setting methodological standards and unblocking the hardest analytical problems across areas including Treasury, Markets, Custody, and XRPL. Partner with product and business leads to define analytics strategy: shaping which initiatives to invest in, what success looks like, and how we'll know. Build the scientific frameworks Ripple reuses at scale: product and network health metrics, causal inference playbooks, liquidity and adoption models, and forecasting approaches that work across institutional and developer surfaces. Pioneer AI-accelerated analytics: applying LLMs and agentic workflows to scale insight generation, automate routine analysis, and enable self-serve exploration for non-DS partners. Drive evidence-based evaluation of growth across customers, corridors, and on-chain activity, surfacing the causal drivers behind adoption and volume. Define and communicate the metrics leadership runs on: translating complex results into clear narratives for Ripple executives and external stakeholders. Raise the bar for the DS function through thought leadership and mentorship across embedded teams.