Senior Associate – Credit Risk

A Leading Global Consultancy is seeking an analytical Senior Associate – Credit Risk to join its financial services practice. In this pivotal role, you will be responsible for building and validating credit risk models to support global banking clients. Furthermore, you will analyze large financial datasets to identify trends and provide actionable risk insights. Consequently, this position is vital for helping our partners maintain regulatory compliance and optimize their credit portfolios.

The Senior Associate – Credit Risk must possess a strong foundation in quantitative modeling and statistical tools. Additionally, you will lead the preparation of technical documentation and collaborate with cross-functional teams to implement risk strategies. Therefore, the consultancy is looking for a professional with 2 to 4 years of experience in risk analytics. If you have a passion for data-driven decision-making and excellence in SQL or Python, this Senior Associate – Credit Risk role offers a premier professional path.

Key Responsibilities

• Develop and maintain Credit Risk models (PD, LGD, EAD) in alignment with IFRS 9 and Basel III standards.
• Analyze complex datasets to identify early warning signals of credit deterioration within portfolios.
• Design and automate risk reporting dashboards to provide real-time insights to senior management.
• Collaborate with global client teams to refine credit underwriting and collections strategies.
• Prepare detailed technical model documentation to meet strict regulatory and audit requirements.
• Perform stress testing and scenario analysis to assess the impact of macroeconomic shifts.
• Ensure high data integrity and accuracy throughout the model development lifecycle.
• Identify and implement process improvements to enhance the efficiency of risk monitoring.
• Liaise with internal stakeholders to align risk analytics with broader business objectives.
• Mentor junior associates and contribute to the firm’s internal risk knowledge repository.

Requirements and Qualifications

• Master’s degree in Statistics, Economics, Finance, or a related quantitative field.
• 2 to 4 years of experience in Credit Risk Analytics or financial modeling.
• Technical proficiency in SQL, Python, or SAS for data manipulation and analysis.
• Strong understanding of credit product lifecycles and retail/wholesale banking.
• Excellent communication skills with the ability to present technical results clearly.