11 May 2026

Lead Data Analyst

ABN AMRO Bank N.V.

Amsterdam

11 May 2026

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Lead Data Analyst

ABN AMRO's Channel Security team is seeking a Lead Data Analyst for its Fraud Monitoring division in Amsterdam. The role involves deep-dive analysis of fraud patterns, methodological leadership to advance analytics maturity, and collaboration with fraud experts and data scientists. Candidates need strong SQL and Python skills, a quantitative master's degree, and at least 3 years of analytical experience.

HybridFull-timeLeadSQLPython

Lead Data Analyst

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HybridFull-timeLeadSQL

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

Hybrid: on-site in Amsterdam with hybrid working according to agile/scrum principles

Experience Required

3 years

Employment Type

Full-time

Experience Level

Lead

Core Qualifications

Technical (Must-have)

SQLPythonPySparkdata analysisfraud detectionstatistical conceptscritical thinkingScrumAgile

Soft Skills

communicationteamworkmentoringproblem solvinganalytical rigorcritical thinking

Key Responsibilities

•Perform in-depth analyses to understand fraud patterns, attack vectors, seasonality, behavioural shifts, and detection performance across payment channels.
•Evaluate the strength of proposed detection logic (features, thresholds, rules) and identify when ideas are overly narrow, unsupported by evidence, or prone to false positives.
•Assess the value and reliability of data fields and signals used in fraud detection.
•Help ensure our reasoning, conclusions, and decisions are analytically sound and well-supported.
•Guide Fraud Experts and junior analysts in applying good analytical practices and critical thinking.
•Coach colleagues on interpreting data responsibly, avoiding common analytical pitfalls, and understanding basic statistical concepts such as variance, sample bias, and signal strength.
•Promote a culture of analytical rigor — ensuring the team adopts more mature, data-driven ways of working.
•Partner with Data Scientists to transform analytical insights into hypotheses, experiments, and feature ideas for model development.
•Act as a bridge between domain experts and technical experts, ensuring clear understanding on both sides.
•Identify opportunities to improve how we measure fraud impact, effectiveness of controls, and operational efficiency.

Lead Data AnalystFraud MonitoringABN AMROAmsterdamSQLPythonPySparkBankingAnalyticsHybrid

Key Responsibilities

•Perform in-depth analyses to understand fraud patterns, attack vectors, seasonality, behavioural shifts, and detection performance across payment channels.

•Evaluate the strength of proposed detection logic (features, thresholds, rules) and identify when ideas are overly narrow, unsupported by evidence, or prone to false positives.

•Assess the value and reliability of data fields and signals used in fraud detection.

•Help ensure our reasoning, conclusions, and decisions are analytically sound and well-supported.

•Guide Fraud Experts and junior analysts in applying good analytical practices and critical thinking.

•Coach colleagues on interpreting data responsibly, avoiding common analytical pitfalls, and understanding basic statistical concepts such as variance, sample bias, and signal strength.

•Promote a culture of analytical rigor — ensuring the team adopts more mature, data-driven ways of working.

•Partner with Data Scientists to transform analytical insights into hypotheses, experiments, and feature ideas for model development.

•Act as a bridge between domain experts and technical experts, ensuring clear understanding on both sides.

•Identify opportunities to improve how we measure fraud impact, effectiveness of controls, and operational efficiency.