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.

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Skills

Agentic Workflow Ai Airflow Analytics Blockchain Causal Inference Crypto Databricks Data Science Dbt Experimentation Fintech Forecasting Llm Mentorship Payments Python Quantitative Analysis R Sql Statistical Modeling

Candidate Availability

Hybrid · San Francisco · Required

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will lead data science methods across product and business areas. You will define analytics strategies, build reusable measurement frameworks, apply AI and agentic workflows, evaluate growth and adoption, develop metrics, communicate findings to executives and stakeholders, and mentor data scientists.

Requirements

8+ years of experience in data science or quantitative analysis
Technical leadership experience across cross-functional teams
Experience designing reusable analytics and measurement frameworks
Hands-on experience applying AI to analytics workflows
Expertise in experimentation causal inference forecasting and statistical modeling
Expertise in Python or R
Fluency in SQL
Experience with large-scale data technologies such as Databricks Airflow and dbt
Experience with FinTech payments crypto or blockchain data preferred
Advanced degree in a quantitative field preferred
Exceptional communication skills

Responsibilities

Set methodological standards across product and business teams
Define analytics strategy with product and business leaders
Build reusable product and network health metrics
Develop causal inference playbooks liquidity models adoption models and forecasting approaches
Apply LLMs and agentic workflows to analytics
Automate routine analysis and enable self-service exploration
Evaluate growth across customers corridors and on-chain activity
Identify causal drivers of adoption and volume
Define and communicate leadership metrics
Translate complex results into clear narratives
Provide thought leadership and mentorship to data scientists

Benefits

Equity compensation
Competitive benefits covering physical and mental healthcare retirement family forming and family support
Employee giving match
Mobile phone stipend
R&R days
Wellness reimbursement
Weekly onsite and virtual wellness programming
Generous vacation policy
Parental leave and family planning benefits
Catered lunches
Fully stocked kitchens
Employee events