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Data Scientist

Sardine

🌍 Europe 🏠 Remote ⏱ Part-time 💼 Mid-level 🗓 1 weeks ago

Who we are:

We are a leader in fraud prevention and AML compliance. Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens. Today, over 300 banks, retailers, and fintechs worldwide use Sardine to stop identity fraud, payment fraud, account takeovers, and social engineering scams. We have raised $145M from world-class investors, including Andreessen Horowitz, Activant, Visa, Experian, FIS, and Google Ventures.

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-fac...

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