Lead Data Scientist - Credit Risk Modeling

Overview

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.

Responsabilità Train transformer-based models on long sequences of transactions

Design tokenisation schemes for heterogeneous features (numerical, categorical, temporal)

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

Collaborate in a small, high-ownership team to deliver impactful solutions

Requisiti fondamentali 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

curiosity

transformer architectures

sequence modelling

tokenisation design for numerical, categorical, and temporal features