Klarna
Senior/Lead Data Scientist -Credit Risk Modeling

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Lead Data Scientist - Credit Risk Modeling
At Klarna, our credit risk models sit at the heart of how we underwrite and price risk for millions of consumers globally. We're looking for a Lead Data Scientist to help shape the next generation of consumer-level credit scoring and portfolio valuation models.
What you'll do
As a Lead Data Scientist within credit risk modeling, you will shape Klarna's next-generation consumer-level credit scoring and portfolio valuation models. You'll design and maintain real-time PD (Probability of Default) models using statistical and ML approaches, integrating them into frameworks for underwriting and economic return optimization. You'll develop calibration frameworks, ensure compliance with regulatory and fairness standards, and explore novel methodologies — including LLMs for explainability and feature engineering. Collaborating with cross-functional teams, you'll translate modeling insights into strategic credit policies and business value, while mentoring junior team members and contributing to Klarna's long-term modeling vision.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Who you are
- 5+ years' experience in credit risk modeling for consumer lending, credit cards, or BNPL.
- Deep proficiency in PD model development and validation, with strong knowledge of calibration techniques.
- Advanced Python and SQL skills; familiar with XGBoost, scikit-learn, pandas, MLFlow.
- Experience with explainability frameworks such as SHAP, LIME, PDP.
- Ability to communicate technical concepts clearly and influence cross-functional decisions.
- Familiarity with real-time modeling and current trends in ML and credit analytics.


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Awesome to have
- Hands-on experience using LLMs to extract features from unstructured data (e.g., customer communications, credit applications).
- Knowledge of integrating third-party credit bureau data into production models.
- Understanding of champion/challenger model frameworks and A/B testing infrastructure.
- Exposure to loan-level economic modeling, including cost-of-capital and loss metrics.
Please include a CV in English
Curious to learn more about Klarna and what it's like to work here? Explore our career site!
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