Data Analyst - Fraud Intelligence

Stack

Responsibilities

• ▹Design and execute structured evaluation frameworks to assess the quality, coverage, and fraud-signal value of incoming vendor data assets
• ▹Build lift analyses, backtests, and champion/challenger comparisons to quantify the incremental value of new data signals against the existing fraud detection stack
• ▹Profile vendor datasets for completeness, freshness, match rates, and population coverage across verticals (crypto, fintech, neobanks, e-commerce)
• ▹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 production-like test environments
• ▹Document evaluation results and maintain an internal knowledge base on vendor data performance
• ▹Support ad hoc deep dives into 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, ideally in fraud, risk, fintech, or a data-heavy B2B SaaS environment
• ▹Proficiency in SQL (required), plus 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, 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, synthesizing 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

Nice to have

• ▹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
• ▹Experience working across fintech verticals such as crypto, BNPL, neobanks, or payments

Soft skills

What we offer

• ▹Generous compensation in cash and equity
• ▹Early exercise for all options, including pre-vested
• ▹Fully remote, work-from-anywhere culture
• ▹Flexible paid time off and year-end break
• ▹Health, dental, and vision coverage for employees and dependents (US/Canada)
• ▹4% matching in 401k/RRSP (US/Canada)
• ▹MacBook Pro delivered to your door
• ▹One-time home office setup stipend (desk, chair, screen, etc.)
• ▹Monthly meal and social meetup stipend
• ▹Annual health/wellness and learning stipend

About the company

Sardine is the leading agentic risk platform for fighting financial crime, unifying data across risk teams to stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations. Its consortium spans more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide. Clients include FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com. The company has hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo, but maintains a remote-first culture.