Credit Models Quant Analyst

We are looking for a motivated quantitative professional with hands-on experience in credit and statistical models within financial services. The successful candidate will be intellectually curious, detail-oriented, and comfortable working across model development, assessment, and documentation — with the ability to present technical findings clearly to both technical and non-technical audiences.

You will thrive in this role if you bring:

1. 2 to 5 years of experience in a financial services firm
2. Prior exposure to statistical models in finance, particularly in a credit or risk context
3. Experience with Borrower Rating models (highly desirable)
4. A highly numerate academic background — Maths, Statistics, Engineering, or Computer Science — at MSc level or above

Candidates should demonstrate strong technical capability across the following areas:

1. Strong knowledge of statistics and quantitative methods
2. Understanding of the theory of default modelling and credit risk frameworks
3. Familiarity with portfolio credit risk models and scenario-based stress testing
4. Experience performing representativeness and performance monitoring analyses
5. Understanding of UK and ECB regulatory expectations for model documentation

1. Proficiency in Python (required)
2. Ability to work with large datasets and model outputs in a structured, reproducible manner

1. Ability to produce clear, well-structured model documentation for technical and regulatory audiences
2. Experience documenting models in line with internal governance and external regulatory standards

We look for consultants who combine technical excellence with the professional behaviours that make a real difference in client environments. The following competencies are essential:

1. Excellent written and verbal communication skills, with the ability to tailor style and content to different audiences — from technical model owners to senior risk stakeholders
2. Confident presenting findings and documentation to both internal teams and regulators

1. Strong analytical mind-set with excellent attention to detail
2. Ability to assess complex model frameworks and identify gaps in applicability or documentation
3. Sound judgement and strong decision-making skills, including in ambiguous situations

1. Highly motivated and able to work on own initiative
2. Strong time management and ability to prioritise across multiple workstreams
3. Able to manage large workloads and tight deadlines, balancing urgent tasks with longer-term deliverables

1. A genuine team player with a professional and constructive attitude
2. Innovative approach to problem-solving, with a willingness to propose and test new approaches

Committed to maintaining high standards of accuracy and quality throughout