Senior Data Scientist
Sardine
| Company | Sardine |
| Category | Data & Analytics |
| Location | United Kingdom |
| Remote | Remote |
| Employment | Not stated |
| Level | Senior |
| Salary | GBP 85k–140k |
| Posted | 29 Apr 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer ATS (ashby) |
Description
Who we are:
Sardine is the leading agentic risk platform for fighting financial crime. Our integrated solution unifies data across risk teams to help organizations stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations. Sardine’s platform is strengthened by one of the fastest-growing fraud consortiums in the market, spanning more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide. Leading companies including FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com rely on Sardine to secure and grow trust in their products.
Our culture:
- We have hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo. However, we maintain a remote-first work culture. #WorkFromAnywhere
- We hire talented, self-motivated individuals with extreme ownership and high growth orientation.
- We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.
Location
- UK, Germany, Ireland, Spain, Poland, Bulgaria and Lithuania - Remote
- From Home / Beach / Mountain / Cafe / Anywhere!
- We are a remote-first company with a globally distributed team. So you can find your productive zone and work from there.
About the role
We're looking for a data-driven professional to help us measure, understand, and improve the performance of our risk strategies — and to stay ahead of evolving fraud threats by designing and deploying data-driven solutions with real-world impact. You'll work directly with clients to understand their unique fraud challenges, rapidly prototype proof-of-concept models, and build scalable, production-ready solutions using machine learning and graph analytics.
You'll also analyze complex datasets, design metrics, build dashboards, and collaborate closely with stakeholders across the business to drive decision-making and optimize outcomes.
This is a hands-on, high-impact role ideal for someone who thrives at the intersection of data science, client-facing problem solving, and real-time risk.
What you'll be doing
- Champion a data-first approach across internal teams and client engagements, promoting clarity and impact
- Build and deploy machine learning models to prevent fraud across diverse fintech use cases, from proof-of-concept through to production
- Develop and track metrics to measure and monitor the performance of our risk products and the effectiveness of risk management strategies
- Conduct in-depth analyses to uncover insights contributing to fraud reduction and higher approval rates for our clients
- Work directly with clients to understand their fraud challenges and translate complex data insights into clear, actionable recommendations
- Use data and models to support the development of risk mitigation strategies and interventions while preserving and improving the user experience
- Create and automate self-serve dashboards leveraging BI tools
- Collaborate with engineering to scale models into production, optimize performance, and support data instrumentation
- Partner with cross-functional teams (Business, Product, and Engineering) to translate business requirements into data-driven solutions
What you'll need
- 7+ years of experience in data science, quantitative modeling, or a data-focused role (product analytics, business analytics) with demonstrated high impact in fraud or risk contexts
- Strong hands-on experience with Python/R and SQL is essential, with Spark being a nice to have
- Expertise in BI tools such as Tableau, Sigma, or Metabase
- Proven ability to structure and analyze complex data using techniques like EDA and cohort analysis, and communicate findings effectively to both technical and non-technical audiences, including clients
- Sharp critical thinking and creative problem-solving skills with a bias toward ac