Note: The job is a remote job and is open to candidates in USA. Sardine is the leading agentic risk platform for fighting financial crime. They are seeking a Data Analyst to join their Fraud Intelligence team, responsible for evaluating, testing, and onboarding new third-party data signals and vendor partnerships to enhance fraud detection capabilities.

Responsibilities

• 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

Skills

• 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
• Familiarity with fraud signals and data types: device fingerprinting, identity graph data, consortium data, behavioral signals, email/phone intelligence
• Experience in a vendor evaluation, data partnerships, or procurement-adjacent analytical role
• Exposure to machine learning concepts and feature engineering, even if not in a full ML engineering capacity
• Experience working across fintech verticals such as crypto, BNPL, neobanks, or payments

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

Company Overview

Company H1B Sponsorship