Staff Data Scientist

You'll be the technical lead across Ripple's diverse product and business portfolio, defining the analytics vision and building the scientific frameworks the org uses to evaluate product and business performance. You'll use AI tooling to accelerate the speed and reach of analytics across the company. You'll partner with product and business leads to frame the most important questions, set the analytical bar, and ensure decisions rest on a consistent, thorough foundation. You'll operate as a force multiplier, solving the hardest problems, building frameworks others reuse, and levelling up data scientists across teams.

Responsibilities

• Serve as 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 and what success looks like
• Build scientific frameworks Ripple reuses at scale, including product and network health metrics, causal inference playbooks, liquidity and adoption models, and forecasting approaches
• Pioneer AI-accelerated analytics by 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 causal drivers behind adoption and volume
• Define and communicate the metrics leadership runs on, translating complex results into clear narratives for executives and external stakeholders
• Raise the bar for the DS function through thought leadership and mentorship across embedded teams

Requirements

• 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

Benefits

• Professional development budget
• In-office collaboration flexibility (10+ days a month)
• Bi-weekly all-company meeting with Leadership Team
• Team offsites, team bonding activities, and happy hours
• Competitive bonuses and equity
• Competitive benefits covering physical and mental healthcare, retirement, family forming, and family support
• Employee giving match
• Mobile phone stipend
• R&R days
• Generous wellness reimbursement and weekly onsite & virtual programming
• Generous vacation policy
• Industry-leading parental leave policies and family planning benefits
• Catered lunches, fully-stocked kitchens with premium snacks/beverages, and fun events