Senior Fraud ML Validation Scientist

Klarna; Milano; Ibrido; EUR 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

Klarna is seeking a second-line validator to assess fraud models and governance across real-time payments and identity checks. You will review large-scale datasets, challenge model choices, and ensure production readiness with CI/CD and cloud tools.

You will work with first-line data scientists and ML engineers, applying governance, bias, privacy, and explainability considerations to scale risk management across Klarna's operations.

Competenze

• 3+ years hands-on in fraud-related modeling (transaction fraud, account takeover, identity, or payments fraud).
• Experience with tree-based models like LightGBM and anomaly/graph modeling.
• End-to-end ML lifecycle experience from feature engineering to production monitoring.
• Fluent Python and SQL; scalable data processing with PySpark.
• Ability to design agentic AI workflows and document model risks clearly.

Mansioni

• Assess model performance using fraud-specific metrics and weigh business trade-offs.
• Review transaction datasets and feature pipelines for representativeness and leakage risk.
• Evaluate drift detection, retraining strategies, and production monitoring practices.
• Assess CI/CD and deployment controls - Docker, Jenkins, and AWS SageMaker/Athena/Lambda environments.
• Evaluate model governance documentation, explainability approaches, and regulatory compliance.
• Validate emerging techniques like graph networks and GenAI-based components.
• Document validation outcomes and communicate model risks to data scientists, ML engineers, and stakeholders.

Conoscenze

LightGBM

Tree models

Python

SQL

PySpark

Spark

Model validation

Explainability

AI governance

Docker

Jenkins

SageMaker

Data quality

Formazione

Master's or PhD in quantitative field

Strumenti

Docker

Jenkins

AWS SageMaker

S3

Athena

Lambda

Descrizione del lavoro

Klarna is seeking a second-line validator to assess fraud models and governance across real-time payments and identity checks. You will review large-scale datasets, challenge model choices, and ensure production readiness with CI/CD and cloud tools.

You will work with first-line data scientists and ML engineers, applying governance, bias, privacy, and explainability considerations to scale risk management across Klarna's operations.