Assistant Manager, Quantitative Risk Analytics & Modelling

RSM; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A global audit and consulting firm is looking for an Assistant Manager to join the Quantitative Analytics & Risk Modelling team in London. The role includes building and validating statistical and machine learning models for credit decisioning, partnering with various teams to ensure robust governance. The ideal candidate has over 3 years of experience in credit risk modelling and possesses skills in Python, SAS, SQL, and machine learning. This position offers a flexible benefits package, including study support and well-being initiatives.

Benefits

Study Support (FRM, CFA)

Hybrid and Flexible working

26 Days Holiday

Lifestyle, Health, and Wellbeing benefits

Access to a suite of 300+ courses

Qualifications

• Minimum of 3 years in credit risk modelling/analytics within a bank, lender, or consulting firm.
• Solid understanding of PD, LGD, EAD, IFRS 9 impairment, and Basel III/IV IRB concepts.
• Ability to translate complex model behaviour into business-friendly narratives.

Responsibilities

• Deliver models that raise approval quality and reduce bad debt.
• Enhance IRB capital estimates and IFRS 9 ECL accuracy.
• Streamline analytics pipelines for faster product iterations.
• Establish clear monitoring and early-warning indicators.
• Produce audit-ready documentation and evidence.

Skills

Credit risk modelling

Statistical analysis

Machine learning

Python

SQL

SAS

R

Dashboarding in Power Bi/Tableau

Education

Bachelor's or Master's in Statistics, Mathematics, Econometrics, Data Science, Computer Science

Job description

A global audit and consulting firm is looking for an Assistant Manager to join the Quantitative Analytics & Risk Modelling team in London. The role includes building and validating statistical and machine learning models for credit decisioning, partnering with various teams to ensure robust governance. The ideal candidate has over 3 years of experience in credit risk modelling and possesses skills in Python, SAS, SQL, and machine learning. This position offers a flexible benefits package, including study support and well-being initiatives.