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 - 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 action - Proficiency in defining, tracking, and communicating performance metrics Benefits we offer: - Generous…