Credit Risk Modeller (Scoring Models/Advanced Analytics/Alternate Data)

SUMMARY:
Are you a credit risk modelling expert with a strong research mindset and proven experience with building robust scoring models? Do you thrive in environments where statistical rigour, creative thinking, and technical excellence drive business decisions? We are partnering with a leading financial services group to appoint a Credit Risk Modeller with a strong focus on developing credit scoring models using traditional and alternative data sources. This is an opportunity to influence credit vetting decisions across the customer lifecycle in a forward-thinking, analytics-led environment.

POSITION INFO:
Credit Risk Modeller – Scoring Models/Advanced Analytics/Alternate Data

Key Responsibilities:

• Design, build and implement credit scoring models (PD, LGD, and IFRS 9) using structured and unstructured/alternate data.
• Develop machine learning and statistical models to enhance the credit vetting process.
• Conduct data mining, feature engineering, and statistical testing across large datasets.
• Work with risk, credit, analytics and technology teams to ensure that models are integrated and performing optimally.
• Research and publish model documentation in alignment with governance and regulatory requirements.
• Engage with internal committees and influence modelling best practices across the business.

• PhD/MSc in Actuarial Science, Data Science, Quantitative Risk, or similar.
• 5+ years of hands-on experience in credit risk modelling, especially within a banking or financial services context.
• Strong foundation in GLMs, survival models, Markov models, or Cox-regression frameworks.
• Highly proficient in R, Python, SQL, and tools such as SAS or Emblem.
• Experience with R Shiny, dashboards, or model explainability tools will be a strong advantage.
• A track record of research publications, technical model development, and involvement in academic or industry collaboration projects is highly valued.

• Shape and influence the modelling roadmap across multiple credit portfolios.
• Join an award-winning team with a track record of innovation in IFRS 9 and survival modelling.
• Work with data science, analytics, and credit risk specialists in a high-impact environment.
• Exposure to cutting-edge research, alternate data strategies, and real-world deployment.
• Flexible hybrid setup with career progression and thought leadership opportunities.