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About the Role
Ripple is seeking a Senior Data Scientist to lead analytics across its product and business portfolio. This role involves building scientific frameworks for performance evaluation, utilizing AI tooling for analysis acceleration, and partnering with product and business leads to address complex, high-impact problems.
Responsibilities
- Serve as the data science lead for product or business areas like Payments, Stablecoin, or Custody.
- Apply strong methodology and tackle the hardest analytical problems within your domain.
- Partner with product and business leads to shape roadmap decisions, including initiative prioritization and success measurement.
- Build scientific frameworks for teams, including product and network health metrics, causal inference, and forecasting.
- Apply AI to accelerate analytics workflows, using LLMs and agentic workflows for insight generation and automation.
- Drive evidence-based evaluation of growth across customers, corridors, and on-chain activity.
- Define and communicate key metrics for teams and leadership.
- Translate complex results into clear narratives for senior stakeholders.
- Raise the bar for the Data Science function through mentorship and by modeling strong analytical practice.
Requirements
- 7+ years in data science or quantitative analysis with a track record of measurable impact.
- Experience as a data science partner to cross-functional teams.
- Track record designing analytics and measurement frameworks adopted by other teams.
- Hands-on experience applying AI to accelerate analytics workflows.
- Strong expertise in experimentation, causal inference, forecasting, and statistical modeling.
- Expertise in Python or R, fluency in SQL, and experience with large-scale data tech (Databricks).
- Experience with FinTech, payments, crypto, or blockchain data is a strong plus.
- Excellent communication skills, able to translate technical depth into clear narratives for senior stakeholders.
Skills
- Python
- R
- SQL
- Databricks
- AI tooling
- LLMs
- Agentic workflows
- Experimentation
- Causal inference
- Forecasting
- Statistical modeling
Location
- CA
Work Type
- Hybrid
Experience Level
- Senior
- 7+ years
Education Level
- Advanced degree (MS, PhD) in a quantitative field preferred
Salary/Compensations
- $172,000—$215,000 USD
Benefits
- Professional development budget
- Competitive salary, 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
- Family planning benefits
- Catered lunches
- Fully-stocked kitchens with premium snacks/beverages
- Fun events
About the Company
- Ripple is building a world where value moves like information does today, improving the global financial system and creating greater economic fairness and opportunity.
- The company offers the opportunity to build in a fast-paced start-up environment with experienced industry leaders.
- Ripple provides a learning environment to dive deep into the latest technologies and make an impact.
- The company fosters an environment where every employee is respected, valued, and empowered.
- In-office collaboration is important, with flexibility for managers and teams to decide on in-office days.
- Bi-weekly all-company meetings include business updates and an Ask Me Anything session with the Leadership Team.
- The company organizes team offsites, bonding activities, happy hours, and other events.
Equal Opportunity
- Ripple is an Equal Opportunity Employer committed to building a diverse and inclusive team.
- The company does not discriminate against qualified employees or applicants based on race, color, religion, gender identity, sex, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.