Quantitative Risk Analyst, Credit Risk Data Management [Assistant/Regular/Senior]

Nordea; Oslo; On-site; NOK 900,000 - 1,300,000; Full time

Job summary

Nordea in Oslo is seeking a Quantitative Risk Analyst to support data-driven risk modelling, governance, and regulatory reporting across the Risk Models Data and Strategy teams.

You will perform root-cause analyses, optimise data flows, and own data used in credit risk models, ensuring data quality and clear documentation for senior management.

Qualifications

• Experience with credit risk modelling, capital reporting and knowledge of BCBS239 and TRIM.
• Proficient in SQL, SAS, Snowflake, Python or equivalent.
• Master’s degree in finance, economics, engineering, physics, mathematics or similar.
• Strong analytical skills with attention to detail; ability to analyse complex data.
• Excellent communication and presentation skills; able to translate business requirements to IT.
• Self‑driven, structured and able to coordinate multiple deliveries.
• Experience with big data is an asset.

Responsibilities

• Root‑cause analysis and reconciliation of data quality issues.
• Optimise data flows and algorithms to improve efficiency.
• Own and manage all data used in credit risk models across the end‑to‑end lifecycle.
• Identify and govern critical data elements using credit risk knowledge and regulatory expectations.
• Maintain the data governance framework, ensuring data quality controls and documenting data lineage.
• Prepare reports and documentation for senior management and external reporting.

Skills

Credit risk modelling

Capital reporting

BCBS239

TRIM

Data governance

Regulatory knowledge

Education

Master's degree in finance, economics, engineering, physics, mathematics

Tools

SQL

SAS

Snowflake

Python

Job description

Position Overview

We are seeking a Quantitative Risk Analyst for our Risk Models Data and Strategy teams. The role includes data analysis, modelling and governance.

Key Responsibilities

• Root‑cause analysis and reconciliation of data quality issues.
• Optimise data flows and algorithms to improve efficiency.
• Own and manage all data used in credit risk models across the end‑to‑end lifecycle.
• Identify and govern critical data elements using credit risk knowledge and regulatory expectations.
• Maintain the data governance framework, ensuring data quality controls and documenting data lineage.
• Prepare reports and documentation for senior management and external reporting.

Qualifications

• Experience with Credit Risk modelling, capital reporting, and knowledge of BCBS239 and TRIM.
• Proficient in SQL, SAS, Snowflake, Python or equivalent.
• Master’s degree in finance, economics, engineering, physics, mathematics or similar.
• Strong analytical skills, attention to detail and ability to analyse complex data.
• Excellent communication and presentation skills; able to translate business requirements to IT.
• Self‑driven, structured and able to coordinate multiple deliveries.
• Experience with big data is an asset.

Location and Requirements

• Only for candidates in Finland: security clearance required.
• Only for candidates in Sweden: consult union information.
• Only for candidates in Poland: include GDPR statement in CV.

Application Deadline

Submit application no later than 09/08/2026.