Job Description

Senior Credit Analyst - 6-Month Contract

Qualifications:

• Bachelor's degree in Finance, Statistics, Mathematics, Economics, or a related field; Masters degree preferred.
• 5+ years of experience in credit risk modeling, data analysis, or business analysis, with a focus on model unpacking and data sourcing.
• Strong understanding of credit risk models and frameworks (e.g., PD, LGD, EAD calculations) and experience with model deployment processes.
• Proficient in data analysis tools and programming languages (e.g., Python, R, SAS, SQL) with a strong aptitude for working with large datasets.
• Excellent communication skills with the ability to present complex information clearly to non-technical stakeholders.
• Proven leadership skills with experience in mentoring and guiding teams.

Responsibilities:

• Data Management: Identify, source, and analyze relevant data required for model deployment. Ensure data integrity and accuracy in credit risk assessments, and map data flows from source to model while identifying gaps and issues.
• Documentation: Create comprehensive documentation of current models and data flows, including methodologies, assumptions, and parameterizations, ensuring compliance with regulatory and internal requirements.
• Stakeholder Collaboration: Collaborate with quantitative analysts and data scientists to enhance model functionality based on data analysis insights and stakeholder feedback.
• Leadership & Team Development: Guide and mentor junior analysts in data analysis techniques and model unpacking methodologies, fostering a culture of continuous improvement and knowledge sharing.
• Project Management: Plan and oversee project timelines and deliverables for model unpacking and data analysis initiatives, and communicate project updates effectively to stakeholders.
• Model Deployment Analysis: Review and unpack deployed credit risk models to assess deployment effectiveness and identify improvement areas.
• Regulatory Awareness: Stay informed on credit risk regulations and industry best practices, ensuring models comply with evolving standards.