Sardine

3 weeks ago

Data Analyst - Fraud Intelligence

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Join the Fraud Intelligence team to evaluate and onboard third-party data signals that improve fraud detection outcomes. You’ll design testing frameworks, run lift analyses and backtests, profile vendor datasets, and define evaluation criteria with fraud leadership. Partner with data engineering to ensure production-like test environments, then translate findings into clear recommendations (adopt, pilot, deprioritize, or decline) and maintain an internal knowledge base.

Location: United States, Canada

Workplace: Remote

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key 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 incremental value against the existing fraud detection stack.
•Profile vendor datasets for completeness, freshness, match rates, and population coverage across fintech and e-commerce verticals.
•Collaborate with fraud leadership to define evaluation criteria tied to real fraud outcomes (false positive rates, catch rates, precision/recall tradeoffs).
•Translate evaluation results into actionable recommendations and partner with data engineering to define ingestion requirements and production-like test environments.

Pay and Benefits

Salary: USD 115,000 - 145,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVision401kRemote WorkPaid LeaveHome OfficeMeal AllowanceLearning BudgetWellness Stipend

Key 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 including precision/recall, AUC/ROC, lift, population distributions, and A/B testing basics.
•Experience working with external or third-party datasets, including assessing data quality, match rates, and signal value.
•Strong written and verbal communication skills to synthesize complex analysis into clear narratives for non-technical stakeholders.

Experience:3-5 yearsFraudRiskFintechB2B SaaS

Skills:CommunicationOwnershipAbility to handle ambiguityStakeholder synthesis

Tech Stack:SQLPythonR

Company Brief

Sardine

Provides fraud prevention and account security solutions using machine learning to detect and block account takeover, payment fraud, and malicious actors for digital platforms and marketplaces.

Industry: Cybersecurity

Website

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Sardine

3 weeks ago

Data Analyst - Fraud Intelligence

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: United States, Canada

Workplace: Remote

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key 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 incremental value against the existing fraud detection stack.
•Profile vendor datasets for completeness, freshness, match rates, and population coverage across fintech and e-commerce verticals.
•Collaborate with fraud leadership to define evaluation criteria tied to real fraud outcomes (false positive rates, catch rates, precision/recall tradeoffs).
•Translate evaluation results into actionable recommendations and partner with data engineering to define ingestion requirements and production-like test environments.

Pay and Benefits

Salary: USD 115,000 - 145,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVision401kRemote WorkPaid LeaveHome OfficeMeal AllowanceLearning BudgetWellness Stipend

Key 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 including precision/recall, AUC/ROC, lift, population distributions, and A/B testing basics.
•Experience working with external or third-party datasets, including assessing data quality, match rates, and signal value.
•Strong written and verbal communication skills to synthesize complex analysis into clear narratives for non-technical stakeholders.

Experience:3-5 yearsFraudRiskFintechB2B SaaS

Skills:CommunicationOwnershipAbility to handle ambiguityStakeholder synthesis

Tech Stack:SQLPythonR

Company Brief

Sardine

Provides fraud prevention and account security solutions using machine learning to detect and block account takeover, payment fraud, and malicious actors for digital platforms and marketplaces.

Industry: Cybersecurity

Website