Quantitative Credit Risk Analyst: Build & Validate Models

SEB; Pargas; On-site; EUR 65,000 - 95,000; Full time

Job summary

SEB in Finland seeks a Quantitative Credit Risk Analyst to develop and review credit risk models using mathematics, statistics and machine learning on large datasets from loan performance, customer data and macro indicators.

You will collaborate with business units, focus on modelling rather than coding, monitor models for regulatory compliance, back-test results, and contribute to data quality and regulatory projects, with strong emphasis on learning and career development.

Qualifications

• Strong background in mathematics, statistics, econometrics, finance.
• Programming in Python or SAS required.
• Ability to work with large datasets and use statistical software.
• Good communication to explain outputs to stakeholders.
• Experience in model development and review within credit risk contexts.
• Familiarity with PD/LGD/CCF modelling and IRB approaches.
• Educational background in statistics, mathematics or econometrics.

Responsibilities

• Development and review of credit risk models aligned with regulations.
• Model using readymade tools and focus on modelling.
• Explain model outputs to diverse stakeholder groups.
• Monitor and back-test credit risk models for accuracy.
• Contribute to data quality and regulatory projects within credit risk.

Skills

Python

SAS

Statistics

Econometrics

Mathematics

Finance

Data visualization

Communication skills

Education

Degree in Mathematics/Statistics/Econometrics

Tools

Statistical software

Data visualization tools

Job description

SEB in Finland seeks a Quantitative Credit Risk Analyst to develop and review credit risk models using mathematics, statistics and machine learning on large datasets from loan performance, customer data and macro indicators.

You will collaborate with business units, focus on modelling rather than coding, monitor models for regulatory compliance, back-test results, and contribute to data quality and regulatory projects, with strong emphasis on learning and career development.