Staff Data Scientist
Ripple provides payments, custody and stablecoin solutions that help financial institutions integrate blockchain and digital assets.
Maintainer signals as of 8/23/2026
Funding history
Investors
Projects
About Ripple
Ripple helps financial institutions transform global payments by providing blockchain-powered infrastructure for cross-border payments, digital asset custody, and stablecoin solutions. With it, users can enable instant settlements, reduce costs, and access new markets. The company was originally founded as OpenCoin in 2012 and rebranded to Ripple in 2015.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will serve as a technical lead across product and business areas, define analytics strategies, and build reusable frameworks for measurement, causal inference, modeling, and forecasting. You will apply AI to analytics workflows, evaluate growth drivers, communicate executive-ready insights, and mentor data scientists.
Requirements
- 8+ years in data science or quantitative analysis
- Technical leadership across cross-functional teams
- Experience designing reusable analytics and measurement frameworks
- Experience applying AI to analytics workflows
- Expertise in experimentation causal inference forecasting and statistical modeling
- Expertise in Python or R and SQL
- Experience with large-scale data technologies such as Databricks Airflow and dbt
- Experience with FinTech payments crypto or blockchain data is a plus
- Advanced degree in a quantitative field is preferred
- Exceptional communication skills
Responsibilities
- Set methodological standards across product and business teams
- Define analytics strategy and success measures
- Build reusable metrics causal inference liquidity adoption and forecasting frameworks
- Apply LLMs and agentic workflows to analytics
- Evaluate growth across customers corridors and on-chain activity
- Communicate metrics and analytical results to executives and stakeholders
- Mentor data scientists across embedded teams
Benefits
- Professional development budget
- Bonuses and equity
- Physical and mental healthcare coverage
- Retirement benefits
- Family forming and family support benefits
- Employee giving match
- Mobile phone stipend
- R&R days
- Wellness reimbursement
- Generous vacation policy
- Parental leave
- Family planning benefits
- Catered lunches
- Stocked kitchens with snacks and beverages
