At a Glance
- Tasks: Lead data science initiatives, define analytics vision, and solve complex problems across teams.
- Company: Join Ripple, a pioneering crypto solutions company transforming the global financial system.
- Benefits: Competitive salary, bonuses, wellness support, and generous vacation policy.
- Other info: Inclusive culture with opportunities for professional development and team bonding activities.
- Why this job: Make a real impact in a fast-paced environment while growing your skills with industry leaders.
- Qualifications: 8+ years in data science, strong technical leadership, and expertise in AI and analytics frameworks.
The predicted salary is between 80000 - 100000 £ per year.
Please note this is for London, UK. At Ripple, we’re building a world where value moves like information does today. 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.
THE WORK
We're looking for a Staff Data Scientist to be the technical lead across Ripple's diverse product and business portfolio. You'll define the analytics vision, build the scientific frameworks the organisation uses to evaluate product and business performance, and use AI tooling to accelerate the speed and reach of analytics across the company. In this role, you'll partner with product and business leads to frame the most important questions, set the analytical bar, and ensure decisions across surfaces rest on a consistent, thorough foundation. You'll operate as a force multiplier—solving the hardest problems, building the frameworks others reuse, and levelling up data scientists across teams.
WHAT YOU’LL DO
- Be the DS tech lead across multiple product and business teams: setting methodological standards and unblocking the hardest analytical problems across areas including Treasury, Markets, Custody, and XRPL.
- Partner with product and business leads to define analytics strategy: shaping which initiatives to invest in, what success looks like, and how we'll know.
- Build the scientific frameworks Ripple reuses at scale: product and network health metrics, causal inference playbooks, liquidity and adoption models, and forecasting approaches that work across institutional and developer surfaces.
- Pioneer AI-accelerated analytics: applying LLMs and agentic workflows to scale insight generation, automate routine analysis, and enable self-serve exploration 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 leadership runs on: translating complex results into clear narratives for Ripple executives and external stakeholders.
- Raise the bar for the DS function through thought leadership and mentorship across embedded teams.
WHAT YOU'LL BRING
- 8+ years in data science or quantitative analysis, with a track record of senior level impact across multiple teams.
- Technical leadership across cross-functional teams, influencing roadmaps and strategy at both executive and execution levels.
- Proven experience designing reusable analytics and measurement frameworks that scale across products.
- Hands‑on experience applying AI to accelerate analytics workflows (agentic analysis, AI‑assisted insight generation, natural‑language data interfaces).
- Deep expertise in experimentation, causal inference, forecasting, and statistical modeling in a product environment.
- Expertise in Python or R, fluency in SQL, and experience with large‑scale data tech (Databricks, Airflow, dBT a plus).
- Experience with FinTech, payments, crypto, or blockchain data is a strong plus.
- Advanced degree (MS, PhD) in a quantitative field preferred.
- Exceptional communication skills — able to turn technical depth into executive‑ready narratives.
WHO WE ARE
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 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 off‑sites, 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.
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.
Staff Data Scientist London, UK employer: ripple
At Ripple, we pride ourselves on being an exceptional employer, offering a dynamic work environment in London where innovation meets collaboration. Our commitment to employee growth is evident through our professional development budget and mentorship opportunities, while our inclusive culture ensures that every team member feels valued and empowered. With competitive salaries, comprehensive benefits, and a focus on work-life balance, Ripple is the perfect place for those looking to make a meaningful impact in the world of finance and technology.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Scientist London, UK
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Staff Data Scientist London, UK
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at ripple, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at ripple. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at ripple
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at ripple!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.