The posting, in Ripple's own words
archived Sep 28, 2026At 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. 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 Senior Data Scientist to drive analytics across Ripple's product and business portfolio. You'll build the scientific frameworks teams use to evaluate product and business performance, and use AI tooling to accelerate the speed and reach of your analysis. In this role, you'll partner with product and business leads to frame the right questions, bring rigor to how they're answered, and make sure decisions rest on a consistent, thorough foundation. You'll take on ambiguous, high-impact problems, build analyses and tooling others can reuse, and raise the analytical bar of the teams you work with.
Read the full posting ↓
What you’ll do:
Serve as the data science lead for one or more product or business areas — Payments, Stablecoin, or Custody — applying strong methodology and tackling the hardest analytical problems in your domain. Partner with product and business leads to shape roadmap decisions: which initiatives to prioritize, what success looks like, and how we'll measure it. Build the scientific frameworks your teams rely on: product and network health metrics, causal inference approaches, and forecasting that holds up across institutional and developer surfaces. Apply AI to accelerate analytics — using and to scale insight generation, automate routine analysis, and make data more self-serve 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 your teams and leadership run on, translating complex results into clear narratives for senior stakeholders. Raise the bar for the DS function through mentorship and by modeling strong analytical practice for the data scientists around you.