Senior Manager - Credit Risk Modelling

Barclay Simpson
Sheffield
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Manager, Global Data Science & AI Innovator

Senior Data Resilience Manager — Data Integrity & Recovery

Senior Insurance Data Strategy & Governance Lead

AI & Data Science Manager / Senior Manager

AI & Data Science Manager / Senior Manager

Senior IT Audit Lead — Data Analytics & Risk Oversight

My client is one of the largest banks in the UK, renowned for their flexible working culture, remote working opportunities, excellent benefits and outstanding internal culture and career progression.


Reporting directly to the Head of IFRS9 and Stress Testing, you will play a critical role in shaping our risk modelling strategy, enhancing issue resolution, and driving actionable business insights.

As part of a build out of the risk modelling team I am looking for an experienced risk modeller to lead a talented team of modellers and data scientists responsible for developing and managing risk and macroeconomic models to forecast the bank’s loss provisions. You’ll have a wide remit that spans all types of models within the credit risk landscape (mainly impairment, stress and climate risk models), with exposure to both Retail and Business banking products and customers. Your team will focus on the development, validation, management, and monitoring of models, ensuring they provide exceptional support to key stakeholders across Risk and Finance.

You will direct delivery of modelling projects across diverse portfolios, adapting to changing demands and priorities, acting as an SME across all relevant projects, delivering detailed technical challenges across retail and business banking portfolios, ensuring models are robust and aligned with best practices.


You will need significant prior experience of advanced credit risk modelling techniques in a leadership role, with an excellent track record of people management, performance coaching and team development. In addition, advanced understanding of PRA regulatory frameworks, risk appetite and cutting edge modelling techniques.

Please note, this role does not offer Visa sponsorship.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.