Data Analyst - Fraud Intelligence
AI risk platform that helps financial institutions prevent fraud, ensure compliance, and detect money laundering through behavioral analysis and device intelligence.
Funding history
Projects
About Sardine
Sardine helps financial institutions prevent fraud and ensure compliance by analyzing user behavior and device intelligence in real-time. Users can detect identity theft, payment fraud, account takeovers, and money laundering while streamlining KYC/AML processes. Sardine provides risk management with AI agents, case management, and regulatory reporting tools.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Join Sardine's Fraud Intelligence team to evaluate vendor data signals and partnerships, build testing frameworks, define fraud-outcome evaluation criteria, translate findings into recommendations, support data engineering ingestion requirements, document vendor performance, and investigate fraud trends, model performance, and client-specific data questions.
Requirements
- 3–5 years of experience in data analysis, data science, or a related analytical role.
- Proficiency in SQL and Python or R for data manipulation, statistical analysis, and visualization.
- Understanding of precision, recall, AUC, ROC, lift, population distributions, and A/B testing.
- Experience evaluating external or third-party datasets, including data quality, match rates, and signal value.
- Strong written and verbal communication skills.
- Comfort with ambiguity and defining structure in a fast-moving environment.
Responsibilities
- Design and execute structured evaluation frameworks for vendor data assets.
- Build lift analyses, backtests, and champion/challenger comparisons.
- Profile vendor datasets for completeness, freshness, match rates, and population coverage.
- Define evaluation criteria tied to fraud outcomes with fraud leadership.
- Translate vendor data findings into actionable recommendations.
- Partner with data engineering on ingestion requirements and production-like test environments.
- Document evaluation results and maintain an internal knowledge base.
- Support deep dives into fraud trends, model performance, and client-specific data questions.
Benefits
- Generous cash and equity compensation
- Early exercise for all options, including pre-vested options
- Flexible paid time off and year-end break
- Health, dental, and vision coverage for employees and dependents in the US and Canada
- 4% 401k or RRSP matching in the US and Canada
- MacBook Pro
- Home office setup stipend
- Monthly meal stipend
- Monthly social meet-up stipend
- Annual health and wellness stipend
- Annual learning stipend
