Staff Data Scientist

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.