Data Scientist

About Sardine

Sardine is a leader in fraud prevention and AML compliance, utilizing device intelligence, behavior biometrics, machine learning, and AI to proactively stop fraud. Serving over 300 banks, retailers, and fintechs globally, Sardine addresses identity fraud, payment fraud, account takeovers, and social engineering scams. The company has secured $145M from prominent investors including Andreessen Horowitz, Activant, Visa, Experian, FIS, and Google Ventures.

Our Culture

Sardine fosters a remote-first work culture, allowing employees to #WorkFromAnywhere, with hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo. The company seeks talented, self-motivated individuals who demonstrate extreme ownership and a high growth orientation, valuing performance over hours worked and promoting a flexible work-life balance.

Location

This is a remote position open to candidates in the US or Canada, offering the flexibility to work from any preferred productive zone, whether it's from home, the beach, a mountain, or a cafe.

About the Data Scientist Role

As a Data Scientist at Sardine, you will be instrumental in developing and deploying data-driven solutions to help clients combat evolving fraud threats. This high-impact role involves direct client engagement to understand unique fraud challenges, rapidly prototyping proof-of-concept models, and building scalable, production-ready solutions using machine learning and graph analytics. You will also contribute to standardizing modeling workflows and collaborating with engineering to optimize backend systems. It's an ideal position for those who excel at the intersection of data science, client problem-solving, and real-time risk management.

What You’ll Be Doing

• Champion a data-first approach across internal teams and client engagements, ensuring clarity and impact.
• Build and deploy machine learning models to effectively prevent fraud across diverse fintech use cases.
• Utilize data and models to support the development of effective risk mitigation strategies while enhancing user experience.
• Work directly with clients to identify challenges and deliver high-impact, data-driven solutions.
• Evolve risk metrics, supporting datasets, and the measurement of causal impact for various initiatives.
• Collaborate closely with engineering to scale models into production and ensure optimal performance.

What You’ll Need

• 5+ years of experience in data science or quantitative modeling, with a strong preference for risk or fraud contexts.
• An advanced degree in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, or Economics.
• Strong working knowledge of programming languages and tools like Python, R, Spark, or SQL.
• Sharp critical thinking and creative problem-solving skills, coupled with a bias toward action.
• Proven ability to clearly explain complex technical findings to both non-technical stakeholders and clients.

Benefits We Offer

• Generous compensation package including cash and equity, with early exercise for all options.
• Remote-first culture with flexible paid time off and an annual year-end break.
• Comprehensive health, dental, and vision coverage for employees and dependents (US and Canada).
• 4% matching for 401k / RRSP (US and Canada).
• Provision of a MacBook Pro and a one-time stipend for home office setup (desk, chair, screen, etc.).
• Monthly stipends for meals, social meet-ups, and annual allowances for health/wellness and learning.

Key skills/competency

• Fraud Prevention
• Machine Learning
• Data Modeling
• Graph Analytics
• Python
• SQL
• Risk Mitigation
• Client Engagement
• Statistical Analysis
• Production Deployment