Credit Modeller

KarachiFull-timePosted Jun 16, 2026

About Milliman

Milliman is one of the world’s largest providers of actuarial and related consulting services, with practices in healthcare, property & casualty insurance, life insurance and financial services, and employee benefits. Established in 1947, Milliman is an independent firm with a global presence. Our Karachi office supports consulting projects across the Middle East and GCC regions.

Key Responsibilities: 

  • Develop and implement credit risk models, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models. 
  • Perform data analysis and statistical modelling to assess credit risk and forecast potential losses. 
  • Gather, manage, and analyze data for model development and validation. 
  • Collaborate with cross-functional teams to integrate credit risk models into business processes and systems. 
  • Prepare comprehensive reports and presentations on model findings, methodology, and performance for senior management and stakeholders. 
  • Stay updated with industry trends, regulatory changes, and best practices in credit risk modelling. 
  • Assist in derivative (Swap) valuation  

Qualifications: 

  • Proven experience in IFRS 9 modelling, PD modelling, and LGD modelling. 
  • Strong knowledge of databases and data management practices. 
  • Proficiency in Excel and PowerPoint for data analysis and presentation. 
  • Excellent analytical and problem-solving skills with attention to detail. 
  • Ability to work collaboratively in a team environment and communicate complex concepts clearly. 

Preferred Skills: 

  • Experience with programming languages such as SQL, Python, R, and VBA. 
  • Familiarity with data visualization tools like Power BI. 
  • Prior experience working at a Big 4 consultancy firm. 
  • Advanced proficiency in Excel, including complex formulas, pivot tables, and data analysis tools. 
  • Strong presentation skills with the ability to convey technical information to non-technical audiences. 
  • Experience in derivative valuation.  

Education:  

 

  • Bachelor's degree in Finance, Economics, Statistics, Mathematics, or a related field. A Master's degree or relevant certification is a plus. 

 

  • CFA 

 

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