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.