Senior Data Scientist at Sardine in North America

Job 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 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. • We're a remote-first team spread across time zones, so no office to report to - work from wherever helps you do your best work. Just a couple of things to keep in mind: pay is based on where you're located, and you'll need to keep a home base in the country you're hired in. So while we love the "coffee shop today, mountains tomorrow" life, this isn't a passport-optional, work-from-anywhere-on-Earth kind of remote - think flexible within your country, not borderless. Location • Remote - USA or Canada 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