Senior Data Scientist, Credit Risk & Finance Models

Klarna

Stockholms kommun

Hybrid

SEK 900,000 - 1,200,000

Full time

3 days ago
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Job summary

Klarna is seeking a Senior Data Scientist or Lead Data Scientist to join Model Risk within Risk Control. You will review and challenge predictive and AI/LLM models across credit scoring, fraud detection, AML/CTF, finance, and operations, and you’ll help build the code base and AI tooling for scalable validation.

You will work with model developers and business stakeholders to identify control weaknesses, push back on weak modelling practices, and ensure strong governance.

Qualifications

  • Hands-on experience building predictive models for credit risk or underwriting.
  • Experience assessing provisioning, impairment, and IFRS9 modelling.
  • Proficient in Python and SQL for building, running, and interrogating models.

Responsibilities

  • Independently review and challenge predictive and AI/LLM models across risk domains.
  • Collaborate with model developers and business users to pinpoint control weaknesses and ensure fixes.
  • Extend code base and tooling to enable broader, deeper model challenge with limited headcount.
  • Prioritize which models and risks to validate based on overall risk exposure.
  • Use your own model-building experience to test assumptions and data quality.

Skills

Python
SQL
Model risk
Credit risk modelling
IFRS9 modelling
PySpark
AWS
Stakeholder communication
Independent challenge

Education

Master's degree in a relevant field

Tools

PySpark
AWS

Job description

Klarna is seeking a Senior Data Scientist or Lead Data Scientist to join Model Risk within Risk Control. You will review and challenge predictive and AI/LLM models across credit scoring, fraud detection, AML/CTF, finance, and operations, and you’ll help build the code base and AI tooling for scalable validation.

You will work with model developers and business stakeholders to identify control weaknesses, push back on weak modelling practices, and ensure strong governance.

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