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About the Role
We are rebuilding our fraud detection systems from the ground up and are looking for data scientists to own the complete pipeline from raw data to production model, impacting hundreds of millions of transactions. Klarna operates with the speed of a startup, offering real ownership and the opportunity to ship models that matter.
Responsibilities
- Build best-in-class machine learning systems from scratch, owning the complete pipeline from raw data through feature engineering, model design, training, and real-time production deployment.
- Convert existing rules-based fraud systems into sophisticated, model-driven architectures operating at scale.
- Build infrastructure from scratch.
- Translate ambiguous business problems into precise technical solutions.
- Bring novel approaches such as graph networks, anomaly detection, and behavioural signals into production.
Requirements
- End-to-end ML ownership across the full stack: data engineering, feature development, model design, training, low-latency production deployment, monitoring, and retraining.
- Strong instinct for when a model is ready for production and when it is not.
- Proven track record of building ML models and pipelines from scratch.
- Experience building real-time or near-real-time inference systems.
- Comfortable with large-scale datasets including hundreds of millions of transactions and high-dimensional feature spaces.
- Strong Python and SQL skills.
- Hands-on experience in scikit-learn, LightGBM, Docker, Jenkins, and modern Python packaging.
- Self-motivated, fast-moving, and creative.
- Communicates precisely across technical and non-technical audiences including senior stakeholders.
- Degree in computer science, physics, applied mathematics, astrophysics, automatic control, mathematics, software engineering, electrical engineering, or a related quantitative field.
- Include a CV in English.
Skills
- Python
- SQL
- scikit-learn
- LightGBM
- Docker
- Jenkins
- Graph networks
- Anomaly detection
- Behavioural signals
- AWS (SageMaker, Lambda, S3, Athena)
- CI/CD practices
Location
- Remote
Work Type
- Full-time
Experience Level
- Mid-level
- Senior
Education Level
- Bachelor's degree in a quantitative field
About the Company
- Klarna is a big company that still moves like a startup: fast decisions, real ownership, and models that ship.
- We own the full stack.
- Fraud is one of the most technically demanding problem spaces at Klarna.