Lead Data Scientist - Credit Risk Modeling

Klarna; Monza; In loco; EUR 70.000 - 110.000; Tempo pieno

Descrizione del lavoro

Klarna is seeking an ML Engineer to tackle technically challenging modelling problems in fintech by training transformer-based models on long sequences of real-world transactional events. You will design tokenisation schemes for numerical, categorical, and temporal features, shaping vocabulary size, sequence length, and information compounding.

You’ll oversee the full model lifecycle from data prep to production, guiding ML direction for the company.

Competenze

• Experience building transformer-based models in production settings.
• Experience designing tokenisation for heterogeneous features.
• Proficiency in Python and PyTorch for model development.
• Hands-on experience with SageMaker and Airflow for ML workflows.
• Track record of end-to-end model lifecycle from data prep to serving.
• Strong problem solving and autonomous in small team settings.

Mansioni

• Train transformer-based models on long sequences of transactions.
• Plan and optimize vocabulary size, sequence length, and information compounding.
• Support end-to-end model lifecycle from data preparation to production serving.
• Translate research decisions into production systems and ML direction for the company.
• Demonstrate deep understanding of transformer architectures and sequence modelling.

Conoscenze

Transformer models

Tokenisation design

Python

PyTorch

SageMaker

Airflow

Production deployment

Fintech domain

Problem solving

Autonomy

Descrizione del lavoro

In this role you will tackle technically challenging modelling problems in fintech by training transformer-based models on long sequences of real-world transactional events. You will design tokenisation schemes for numerical, categorical, and temporal features, shaping vocabulary size, sequence length, and information compounding. You’ll oversee the full model lifecycle from data prep to production, translating research decisions into systems that steer ML at Klarna. You join a small, high-ownership team where your work directly impacts Klarna’s products. This is a mission-driven opportunity to shape scalable ML infrastructure in fintech.

• Train transformer-based models on long sequences of transactions
• Plan and optimize vocabulary size, sequence length, and information compounding
• Support end-to-end model lifecycle from data preparation to production serving
• Translate research decisions into production systems and ML direction for the company
• Deep understanding of transformer architectures and sequence modelling
• Experience designing tokenisation for heterogeneous features
• Proficiency in Python, PyTorch, SageMaker, and Airflow
• Experience owning the full model lifecycle from training to serving in production
• Ability to work on open-ended technical problems in a small team
• autonomy
• problem-solving
• tokenisation design for numerical, categorical, and temporal features