Graduate Credit Risk Modeller

Barclay Simpson; Greater London; On-site; GBP 25,000 - 35,000; Full time

Job summary

Barclay Simpson in London is seeking a graduate or early-career analyst to join its credit risk modelling team. You will prepare and analyse datasets, support model development and testing, and explain results to stakeholders.

No prior credit risk experience is required; the role emphasizes strong quantitative ability, practical Python skills, and the ability to take a project from analysis to conclusions, including IFRS 9 or IRB models and scorecards.

Qualifications

• A BSc or MSc in a quantitative subject. An MSc is preferred and a 2:1 or above is typical.
• Up to one year of professional experience; final-year students and recent graduates are welcome.
• Python skills demonstrated through a dissertation, GitHub, placement or personal project.
• Experience cleaning and analysing data, and communicating what the results mean.
• Curiosity, attention to detail and a willingness to learn.

Responsibilities

• Prepare and analyse datasets, support model development and testing, and explain results.
• Contribute to technical documentation and client discussions, and learn how to present findings.
• Work on IFRS 9 models, IRB models, credit scorecards and model validation as needed.

Skills

Quantitative ability

Data cleaning & analysis

Communication of results

Curiosity & willingness to learn

Attention to detail

Education

BSc or MSc in quantitative subject

MSc preferred, 2:1 or above

Tools

Python

SQL

pandas

scikit-learn

Job description

If you enjoy working with data and want to see how quantitative models are used in real lending decisions, this is an opportunity to build your career in credit risk.

We are recruiting for a consulting firm seeking a graduate or early-career analyst to join its modelling team. You will work closely with experienced colleagues on projects for financial services clients, with support as you develop your technical skills.

You do not need previous credit risk experience. The team is looking for strong quantitative ability, practical Python skills and evidence that you can take a project from initial analysis through to a clear conclusion.

The role

You will prepare and analyse datasets, support model development and testing, check and explain results, and contribute to technical documentation. The work may include IFRS 9 models, IRB models, credit scorecards and model validation. You will also have opportunities to join client discussions and learn how to present your findings.

What you’ll bring

• A BSc or MSc in a quantitative subject such as mathematics, statistics, physics, econometrics, engineering or computer science. An MSc is preferred, and a 2:1 or above is typical.
• Up to one year of professional experience. Final-year students and recent graduates are welcome.
• Python skills you can demonstrate through a dissertation, GitHub repository, placement or personal project.
• Experience cleaning and analysing data, and communicating what the results mean.
• Curiosity, attention to detail and a willingness to learn.

Knowledge of credit risk, financial services, SQL, pandas or scikit-learn would be helpful, but is not essential.