Leads data science across product and business areas, developing metrics, causal inference methods, forecasting models, and reusable analytics tooling. Partners with product and business leaders to guide roadmaps, evaluate growth, and communicate insights. Applies LLMs and agentic workflows to automate analysis and improve self-service analytics. Requires strong statistical modeling, experimentation, Python or R, SQL, Databricks, cross-functional influence, and mentorship experience.
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.
- 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.
For positions that will be based in NY, the annual salary range for this position is below. Actual salaries may vary based on numerous factors including, among other things, an individual applicant’s experience and qualifications for the position. This range does not include equity or additional compensation, such as bonuses or commissions.
NY Annual Base Salary Range
$164,000—$205,000 USD
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.
Ripple is an Equal Opportunity Employer. We’re committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of 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.
Please find our UK/EU Applicant Privacy Notice and our California Applicant Privacy Notice for reference.
Ripple New York, New York, USA Office
155 West 23rd Street, New York, New York, United States, 10011
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Machine Learning • Analytics • Biotech • Generative AI
Lead real-world evidence studies for pharmaceutical clients using complex clinical, molecular, claims, EHR, and registry data. Design observational analyses, derive endpoints, apply survival analysis and causal inference methods, interpret results, and communicate findings to technical and non-technical stakeholders. Develop reusable analytical code and standards while incorporating LLMs and agentic workflows into research processes. Collaborate cross-functionally to improve data quality, products, and RWE methodologies, with a focus on oncology and clinical development.
Top Skills:
Agentic FrameworksAWSBigQueryClaude CodeCursorGithub CopilotGoogle Cloud Platform (Gcp)Large Language Models (Llms)Machine LearningRSQL
HR Tech • Payments • Professional Services • Software
Lead end-to-end data science and machine learning initiatives, from identifying business use cases and querying data through prototyping, evaluation, deployment, and monitoring. Partner with Product, Engineering, and Machine Learning Engineering teams across areas such as risk, insurance, and payments. Develop predictive models, statistical methods, deep learning, and LLM solutions while contributing reusable data assets, tooling, MLOps strategy, technical reviews, and data-informed business decisions.
Top Skills:
DbtDeep LearningLarge Language ModelsMachine LearningMlopsPythonSnowflakeSQLStatistical Modeling
Financial Services
Lead customer insights and big data analytics initiatives for Chase Merchant Services. Build scalable datasets and pipelines with Python and SQL, develop quantitative analyses, and deliver commercially actionable recommendations. Design and evaluate prompts, LLM-powered assistants, retrieval strategies, and agent workflows. Monitor GenAI performance, improve solution quality, and collaborate with product managers, engineers, data owners, subject matter experts, and senior stakeholders.
Top Skills:
Agentic AiAWSGenerative AiLarge Language Models (Llms)PythonSnowflakeSQL
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
