Senior Product Data Analyst (Fraud Platform)
Senior Product Data Analyst – Fraud Analytics & Machine Learning – Fraud Platform
Join our Data Insights team supporting the Fraud Platform to help detect and stop fraud in real time - without slowing down good users. You’ll be instrumental in analyzing telemetry, risk scoring, and fraud countermeasures to reduce fraud attacks and improve accuracy across our detection systems.
You’re a Great Fit If You...
- Have 3+ years of experience in analytics or applied data science, ideally in fraud, risk, or security.
- Are fluent in SQL and comfortable coding in Python.
- Are experienced in Tableau (or a similar BI tool), and can turn complex fraud patterns into actionable visualizations.
- Understand telemetry, feature engineering, and risk scoring concepts.
- Communicate effectively with engineers and policy stakeholders alike.
- Can reason across user behavior and adversarial tactics.
- Thrive in ambiguity and fast response environments.
Bonus Points If You...
- Have built and/or deployed fraud-scoring, anomaly-detection, or predictive-alerting models.
- Have worked in fintech, security, or trust and safety domains.
- Are familiar with streaming data or real-time alerting.
- Enjoy bridging product analytics and machine learning – turning models into practical, measurable impact.
Join our Data Insights team supporting the Fraud Platform to help detect and stop fraud in real time—without slowing down good users. You’ll be instrumental in analyzing telemetry, risk scoring, and fraud countermeasures to reduce fraud attacks and improve accuracy across our detection systems.
You’ll help us protect honest people online by:
- Translate data into action: Deliver insights that help reduce false positives and detect emerging fraud patterns.
- Drive product clarity: Track and report on key fraud metrics – detection accuracy, latency, and escalation volume – and propose data-driven improvements.
- Unlock opportunities: Identify accuracy gaps and design interventions in scoring logic, telemetry features, or ML model thresholds.
- Champion data quality: Define and uphold reliable metric standards across the fraud detection ecosystem.
- Prototype and validate models: Use Python and statistical/ML libraries to create your own and back-test fraud-scoring or anomaly-detection models before production hand-off.
- Support scalable infrastructure: Build dashboards and automated alerting systems that monitor fraud signals and trigger early-warning alerts.
- Work cross-functionally: Partner with Product, Engineering (including Data Scientists), and Fraud Operations teams to ensure models and analytics reduce fraud without hurting user experience.
You are the right future Veriffian for the job if you:
- Have 3+ years of experience in analytics or applied data science, ideally in fraud, risk, or security.
- Are fluent in SQL and comfortable coding in Python.
- Are experienced in Tableau (or a similar BI tool), and can turn complex fraud patterns into actionable visualizations.
- Understand telemetry, feature engineering, and risk scoring concepts.
- Communicate effectively with engineers and policy stakeholders alike.
- Can reason across user behavior and adversarial tactics.
- Thrive in ambiguity and fast response environments.
You’re an especially awesome match if you have:
- Have built and/or deployed fraud-scoring, anomaly-detection, or predictive-alerting models.
- Have worked in fintech, security, or trust and safety domains.
- Are familiar with streaming data or real-time alerting.
- Enjoy bridging product analytics and machine learning – turning models into practical, measurable impact.
Why Veriff?
- Flexibility to work from home
- Stock options that ensure your share in our success
- Extra recharge days on top of your annual vacation
- Extensive medical, dental, and vision insurance to ensure you’re feeling great physically and mentally
- Learning and Development & Health and Sports budget that you are free to tailor to your own needs
- Four weeks of fully paid sabbatical leave after reaching your 5th work anniversary
Location
Preferred: Estonia → Spain → Rest of Europe