Credit Modeller

Milliman, a leading global provider of actuarial and consulting services, operates across healthcare, property & casualty insurance, life insurance, financial services, and employee benefits. Founded in 1947, the firm maintains its independence while serving clients worldwide. The Karachi office plays a vital role in supporting consulting projects throughout 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).
- Conduct data analysis and statistical modeling to evaluate credit risk and forecast potential losses.
- Collect, manage, and analyze data essential for model development and validation.
- Collaborate with cross-functional teams to embed credit risk models into business processes and systems.
- Prepare detailed reports and presentations outlining model methodologies, findings, and performance for senior management and stakeholders.
- Keep abreast of industry trends, regulatory updates, and best practices in credit risk modeling.
- Assist in the valuation of derivatives, specifically swaps.

Required Qualifications

- Demonstrated experience in IFRS 9 modeling, including PD and LGD models.
- Strong understanding of databases and data management techniques.
- Proficiency in Excel and PowerPoint for data analysis and presentation purposes.
- Excellent analytical and problem-solving abilities with a keen eye for detail.
- Effective communication skills and the ability to work collaboratively within a team environment.

Preferred Qualifications and Benefits

- Experience with programming languages such as SQL, Python, R, and VBA.
- Familiarity with data visualization tools like Power BI.
- Previous experience at a Big 4 consultancy firm is highly desirable.
- Advanced Excel skills, including complex formulas, pivot tables, and data analysis functions.
- Strong presentation skills capable of translating technical information for non-technical audiences.
- Experience in derivative valuation adds significant value.

Education

A Bachelor’s degree in Finance, Economics, Statistics, Mathematics, or a related discipline is required. A Master’s degree or relevant professional certifications, such as the CFA designation, are considered advantageous.