Senior Data Scientist

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

Remote - USA or Canada

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