Data Scientist

Numbers tell stories, and in credit risk, those stories decide how a bank understands its customers. We're looking for a Data Scientist to join our IFRS9/Modelling team and help shape the models that measure risk for over a million customers across six countries. If you enjoy the mix of modelling, engineering, and real-world impact, this could be your next chapter.

Introduction to the team:
We are the IFRS9/Modelling team, and credit risk sits at the heart of how we run the bank. We build the models that quantify expected credit losses, and the in-house engine that turns them into the bank's monthly figures - covering unsecured loans, credit cards, and credit lines across Norway, Sweden, Denmark, Finland, Germany, and Spain. Right now, we're moving that engine from on-premises to Databricks on Azure, and shaping how we build in the cloud.

About the role:
As a Data Scientist, you develop the credit risk models behind our customers' risk profiles and help maintain the engine that puts them into production. You'll move between modelling, engineering, and analysis, and see your work through from data to decision.

What you'll do:

• Develop, validate, implement, and simulate credit risk models, PD scorecards, LGD, EAD, staging, and macroeconomic adjustment

• Implement models as production code in our ECL engine, including unit tests and code review

• Build and maintain risk monitoring, forecasting, and reporting tools

• Document models and implementations to the standard our validators, auditors, and regulators expect

• Query and prepare the data behind all of the above (mostly SQL)

• Help complete and improve our move to Databricks on Azure

• Carry out analytical work and present results to technical and business audiences

• Collaborate with IT, Finance, Marketing, and other departments

Who we're looking for:
You're structured, turning recurring tasks into documented procedures you keep refining. You're at home in complex systems, tracing results back to their cause. You're accountable, curious, and self-driven, equally comfortable working solo or as part of a team, and used to juggling parallel projects within a monthly reporting cycle.

Beyond this, we're looking for someone with:

• Higher education in a quantitative subject

• Around two to three years of relevant working experience (a PhD or research experience counts)

• Solid Python for data work: pandas, numpy, scipy - from first analysis through to production code

• Confidence writing your own SQL, or readiness to pick it up quickly

• A habit of maintainable code and clear documentation with version control, tests, and code review

• Strong written and spoken English, including presenting to specialists and non-specialists alike

Strongly preferred: experience with credit scoring or scorecard modelling (binning, WoE, logistic regression, calibration, Gini/PSI monitoring), and banking or credit risk experience.

A plus: IFRS9 models, Databricks/Azure or other cloud platforms, CI/CD pipelines, and fluent in Norwegian, Swedish, or Danish.

You don't need to tick every box, if most of this sounds like you, we'd love to hear from you.

In addition to this, it is important to us that you recognize yourself in our values: we are wholehearted, we collaborate and we take the lead.

Practical information:

• Start: As soon as possible

• Location: Snarøyveien 36, Fornebu

• Form of employment: Full time

• For this position, we conduct a credit check on the candidate we offer the job to. Employment is contingent upon a satisfactory result.

Have you heard of NOBAVERSE?
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If you have any questions or concerns about the position, please contact the responsible recruiter.

We look forward to receiving your application! 🙏✨