Data Analyst (Fintech)

TL;DR

Data Analyst (Fintech): Assessing, testing, and onboarding third-party data signals to enhance fraud detection capabilities with an accent on vendor data evaluation and statistical lift analysis. Focus on building rigorous testing frameworks, quantifying the incremental value of new data assets, and translating complex findings into actionable fraud intelligence.

Location: Must be based in the United States or Canada

Salary: $115,000 – $175,000 (USD/CAD equivalent)

Company

Sardine is a leading agentic risk platform that unifies data to help organizations stop fraud in real time and automate AML operations.

What you will do

• Design and execute structured evaluation frameworks to assess the quality and fraud-signal value of vendor data.
• Build lift analyses, backtests, and champion/challenger comparisons to quantify the value of new data signals.
• Profile vendor datasets for completeness, freshness, and match rates across various fintech verticals.
• Collaborate with fraud leadership to define evaluation criteria tied to real fraud outcomes like precision and recall.
• Translate vendor data findings into clear recommendations for adoption or deprioritization.
• Partner with data engineering to define ingestion requirements and ensure production-like test environments.

Requirements

• Must be based in the United States or Canada
• 3–5 years of experience in data analysis or data science within fraud, risk, or fintech environments.
• Proficiency in SQL and Python or R for statistical analysis and data manipulation.
• Solid understanding of evaluation metrics including precision/recall, AUC/ROC, and A/B testing.
• Experience assessing third-party datasets, including match rates and data quality.
• Strong communication skills with the ability to synthesize complex analysis for non-technical stakeholders.

Nice to have

• Familiarity with fraud signals like device fingerprinting, identity graphs, or behavioral signals.
• Experience in vendor evaluation or procurement-adjacent analytical roles.
• Exposure to machine learning concepts and feature engineering.
• Experience working across fintech verticals such as crypto, BNPL, or neobanks.

Culture & Benefits

• Remote-first culture with a globally distributed team.
• Generous compensation package including cash and equity.
• Comprehensive health, dental, and vision insurance for employees and dependents.
• 4% matching in 401k or RRSP.
• Flexible paid time off and year-end break.
• Stipends for home office setup, meals, social meet-ups, and professional learning.