Senior Data Scientist
Ripple
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Questions you are likely to be asked
- Why do you want to join Ripple?
- What is your experience with R? Tell me one thing you learned the hard way.
- Tell me about a time the data was messy or wrong. What did you do?
- How would you explain your model's result to someone who is not technical?
- What would you check first if a model's accuracy dropped after going live?
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Practise the Senior Data Scientist at Ripple interview free →At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.
If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value.
At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.
If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value.
The work:
We're looking for a Senior Data Scientist to drive analytics across Ripple's product and business portfolio. You'll build the scientific frameworks teams use to evaluate product and business performance, and use AI tooling to accelerate the speed and reach of your analysis.
In this role, you'll partner with product and business leads to frame the right questions, bring rigor to how they're answered, and make sure decisions rest on a consistent, thorough foundation. You'll take on ambiguous, high-impact problems, build analyses and tooling others can reuse, and raise the analytical bar of the teams you work with.
What you’ll do:
- Serve as the data science lead for one or more product or business areas — Payments, Stablecoin, or Custody — applying strong methodology and tackling the hardest analytical problems in your domain.
- Partner with product and business leads to shape roadmap decisions: which initiatives to prioritize, what success looks like, and how we'll measure it.
- Build the scientific frameworks your teams rely on: product and network health metrics, causal inference approaches, and forecasting that holds up across institutional and developer surfaces.
- Apply AI to accelerate analytics — using LLMs and agentic workflows to scale insight generation, automate routine analysis, and make data more self-serve 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 your teams and leadership run on, translating complex results into clear narratives for senior stakeholders.
- Raise the bar for the DS function through mentorship and by modeling strong analytical practice for the data scientists around you.
What you'll bring:
- 7+ years in data science or quantitative analysis, with a track record of measurable impact on product and business decisions.
- Experience as the data science partner to cross-functional teams, shaping roadmaps and helping leaders make better-informed calls.
- Track record designing analytics and measurement frameworks that other teams adopt and build on.
- Hands-on experience applying AI to accelerate analytics workflows — agentic analysis, AI-assisted insight generation, natural-language data interfaces.
- 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.
- Advanced degree (MS, PhD) in a quantitative field preferred.
- Excellent communication skills — able to translate technical depth into clear narratives for senior stakeholders.
WHO WE ARE:
Do Your Best Work
- The opportunity to build in a fast-paced start-up environment with experienced industry leaders
- A learning environment where you can dive deep into the latest technologies and make an impact. A professional development budget to support other modes of learning.
- Thrive in an environment where no matter what race, ethnicity, gender, origin, or culture they identify with, every employee is a respected, valued, and empowered part of the team.
- In-office collaboration for moments that matter is important to our culture, and we give managers and teams the flexibility to decide which 10+ days a month they come in.
- Bi-weekly all-company meeting - business updates and ask me anything style discussion with our Leadership Team
- We come together for moments that matter which include team offsites, team bonding activities, happy hours and more!
Take Control of Your Finances
- Competitive salary, bonuses, and equity
- Competitive benefits that cover physical and mental healthcare, retirement, family forming, and family support
- Employee giving match
- Mobile phone stipend
Take Care of Yourself
- R&R days so you can rest and recharge
- Generous wellness reimbursement and weekly onsite & virtual programming
- Generous vacation policy - work with your manager to take time off when you need it
- Industry-leading parental leave policies. Family planning benefits.
- Catered lunches, fully-stocked kitchens with premium snacks/beverages, and plenty of fun events
Benefits listed above are for full-time employees.
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Listed on arbeitnow · posted 2026-09-30. ApplySarthi collects openings and links to application pages; the role is advertised by Ripple, not by us.