Data Analyst – Fraud Intelligence

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Sardine

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

🔒 Cybersecurity

📋 Compliance

💳 Fintech

Cybersecurity • Compliance • Fintech

Sardine is a cutting-edge platform focused on fraud prevention and compliance. The company offers a behavior-based system for fraud detection, identity verification, and transaction monitoring that helps leading banks, online retailers, and fintechs protect themselves from scams and financial crime. Sardine's technology integrates advanced behavioral biometrics and device intelligence to combat identity fraud, payment fraud, and account takeovers. The platform also streamlines compliance checks such as KYC (Know Your Customer) and AML (Anti-Money Laundering) transaction monitoring. Sardine's comprehensive solution empowers its clients to automate risk decisioning, identify high-risk users early, and manage fraud across the customer journey effectively.

📋 Description

• Design and execute structured evaluation frameworks to assess the quality, coverage, and fraud-signal value of incoming data assets from vendor partners • Build lift analyses, backtests, and champion/challenger comparisons to quantify the incremental value of new data signals against our existing fraud detection stack • Profile vendor datasets for completeness, freshness, match rates, and population coverage across verticals (crypto, fintech, neobanks, e-commerce, etc.) • Collaborate with fraud leadership to define evaluation criteria tied to real fraud outcomes — false positive rates, catch rates, precision/recall tradeoffs • Translate vendor data findings into clear, actionable recommendations: adopt, pilot, deprioritize, or decline • Partner with data engineering to define ingestion requirements and ensure test environments reflect production-like conditions • Document evaluation results and maintain an internal knowledge base on vendor data performance over time • Support ad hoc deep dives into fraud trends, model performance, and client-specific data questions as needed

🎯 Requirements

• 3–5 years of experience in data analysis, data science, or a related analytical role — ideally in fraud, risk, fintech, or a data-heavy B2B SaaS environment • Proficiency in SQL (required) and Python or R for data manipulation, statistical analysis, and visualization • Solid understanding of evaluation metrics and statistical concepts: precision/recall, AUC/ROC, lift, population distributions, and A/B testing basics • Experience working with external or third-party datasets — assessing data quality, match rates, and signal value • Strong written and verbal communication skills; ability to synthesize complex analysis into clear narratives for non-technical stakeholders • Comfort with ambiguity and the ability to define your own structure in a fast-moving environment

🏖️ Benefits

• Generous compensation in cash and equity • Early exercise for all options, including pre-vested • Work from anywhere: Remote-first Culture • Flexible paid time off and Year-end break • Health insurance, dental, and vision coverage for employees and dependents - *US and Canada specific* • 4% matching in 401k / RRSP - *US and Canada specific* • MacBook Pro delivered to your door • One-time stipend to set up a home office — desk, chair, screen, etc. • Monthly meal stipend • Monthly social meet-up stipend • Annual health and wellness stipend • Annual Learning stipend