Senior/Lead Data Scientist -Credit
Most applications go out cold — see where you stand first. No sign-up to start.
Don't just apply. Show up ready.
Olive works from this exact posting — no sign-up to start.
At a glance
Job overview
Klarna is hiring a Senior/Lead Data Scientist -Credit. The role involves tackling technically interesting fintech modelling problems by training large transformer-based models on long sequences of real-world transactional events, designing tokenisation schemes for diverse feature types, and managing the full model lifecycle from data preparation to production, influencing how machine learning operates across Klarna.
Key focus areas include Work on technically interesting modelling problems in fintech using large transformer-based models on long sequences of transactional events, Design tokenisation schemes for numerical, categorical, and temporal features, deciding vocabulary size and sequence length, and Translate research decisions into systems that guide machine learning operations across Klarby.
Successful candidates bring CV In English. Important skills include Transformer Architectures, Sequence Modelling, Architectural Tradeoffs, Designing Tokenisation Schemes, Python, and PyTorch. Preferred (not required): Triton Kernels, GPU-Level Optimisation, Broader ML Background, and Large-Scale Transactional Data.
Skills & qualifications
Skills
Qualifications
Full job description
What you will do You will work on some of the most technically interesting modelling problems in fintech, training large transformer-based models on long sequences of real-world transactional events. You will design tokenisation schemes for numerical, categorical, and temporal features, making deliberate decisions about vocabulary size, sequence length, and information compounding. Your work spans the full model lifecycle from data preparation through to production and you will translate research decisions into systems that set the direction for how machine learning operates across Klarna. You will be part of a small, high-ownership team where what you build has genuine impact on the products Klarna ships. Who you are
-
Deep understanding of transformer architectures and sequence modelling, with the ability to reason through architectural tradeoffs
-
Hands-on experience designing tokenisation schemes for heterogeneous feature types such as numerical, categorical, and temporal
-
Proficiency in Python, PyTorch, SageMaker, and Airflow
-
Experience owning the full model lifecycle, from training through to serving in production
-
Comfortable working in a small, high-ownership team on open-ended technical problems
Awesome to have
-
Experience with Triton kernels or GPU-level optimisation
-
Broader ML background spanning areas beyond deep learning
-
Experience with large-scale transactional or financial data
-
Background in ML infrastructure or MLOps
Please include a CV in English Curious to learn more about Klarna and what it's like to work here? Explore our career site !
You've read the whole posting — now see how you match it.