Ripple Staff Data Scientist at Ripple leading analytics vision and frameworks across product and business teams. Use AI tooling to accelerate analytics and partner with product leads to define strategy and metrics.
Responsibilities
Be the DS tech lead across multiple product and business teams: setting methodological standards and unblocking the hardest analytical problems across areas including Payments, Stablecoin & Custody products.
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).
