Credit Risk Modeller – Data-Driven Modeling

Paragon Banking Group PLC; Metropolitan Borough of Solihull; Híbrido; GBP 55.000 - 75.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Generous holiday

Share Save Scheme

Profit Related Pay

Pension Plan

Family Friendly policies

Employee Discounts

Volunteering Day

Life Assurance

Descripción de la vacante

Paragon Banking Group PLC is seeking an experienced Credit Risk Modeller to support the development, validation, and monitoring of credit risk models in line with governance standards. The role focuses on robust analyses, data integrity, and efficient programming to deliver reliable model outputs.

The ideal candidate has a maths/statistics degree and is proficient with R/SQL/SAS/SPSS, with strong communication and reporting skills. Hybrid working is available.

Formación

• Degree level qualification in Mathematics, Statistics or equivalent.
• Experience with R, SPSS, SAS or SQL is preferred.
• Interest in data and problem solving.
• Strong interpersonal and reporting skills.
• Understanding of credit risk management and/or credit scoring is desirable.

Responsabilidades

• Support development, validation, implementation and monitoring of credit risk models per governance standards.
• Perform detailed analyses and validate modelling results for accuracy and sensitivity.
• Specify, implement and maintain model supporting databases; monitor data integrity.
• Create regular monitoring of model stability and remedial action plans.
• Develop efficient, well-documented programs for modelling tasks.

Conocimientos

Curiosity and problem solving

Interpersonal skills

Presentation and report writing

Educación

Degree in Mathematics or Statistics or equivalent

Herramientas

R

SPSS

SAS

SQL

Descripción del empleo

Paragon Banking Group PLC is seeking an experienced Credit Risk Modeller to support the development, validation, and monitoring of credit risk models in line with governance standards. The role focuses on robust analyses, data integrity, and efficient programming to deliver reliable model outputs.

The ideal candidate has a maths/statistics degree and is proficient with R/SQL/SAS/SPSS, with strong communication and reporting skills. Hybrid working is available.