Overview
In this role you lead the productionization of consumer credit underwriting models, turning data-science experiments into reliable, scalable production pipelines. You own the ML infrastructure and deployment, working with a cross‑functional team across Stockholm, Milan and Warsaw to grow Klarna’s in‑house data science capability in credit risk and fraud. You’ll build and maintain the end-to-end ML pipeline, from feature computation to retraining and monitoring, delivering robust models in production. This is a hands-on engineering role focused on delivering impactful, scalable solutions in a fast‑paced fintech environment.
Responsabilità
- Write production Python to train credit underwriting models (tree-based models)
- Build and maintain ML pipeline infrastructure from feature computation through retraining and monitoring
- Deploy models into production using tools like AWS SageMaker and ensure ongoing operation
- Troubleshoot end-to-end pipeline issues and own the lifecycle of deployed models
- Scale Klarna's in-house data science capability as the credit risk and fraud teams grow
Requisiti fondamentali
- Production Python for ML: training models, not just prototyping
- Experience taking ML models/pipelines from development to production and owning them
- Hands-on with tree-based models
- Deployment and operation of ML workloads on AWS or equivalent cloud
- Understanding full SDLC and applying it to ML code
- Collaboration with data scientists to build reliable pipelines
- English communication (spoken and written)
- Clear communication
- Cross-functional collaboration
- Ownership and accountability
- Python for ML (production)
- Tree-based models
- AWS SageMaker or equivalent cloud deployment
Senior Machine Learning Engineer - Credit modelling datore di lavoro: Klarna
Klarna è un datore di lavoro eccezionale, offrendo un ambiente stimolante dove gli ingegneri possono affrontare sfide uniche e significative nel settore finanziario. Con una cultura del lavoro collaborativa e flessibile, i dipendenti hanno l'opportunità di crescere professionalmente, contribuendo a progetti innovativi che utilizzano l'IA. Inoltre, la posizione in un contesto internazionale permette di lavorare con team diversificati, arricchendo ulteriormente l'esperienza lavorativa.
