Senior Assistant Vice President

Role: Lead - IFRS 9 Model Development and Decision Scorecard Teams

We are seeking a dynamic professional to lead our IFRS 9 Model Development and Decision Scorecard (Acquisitions, Behavioral, Collections) Development teams. This role involves delivering data-driven credit risk solutions for a leading bank, with a primary focus on IFRS 9 models. The ideal candidate will bring expertise in end-to-end model development, compliance, and providing actionable insights to solve complex client challenges.

Key Responsibilities:

• Problem Solving: Identify and frame analytical challenges related to regulatory risk and modeling. Develop hypotheses, research data attributes, and determine effective solutions.
• Data Preparation: Extract, clean, and prepare data for analysis, ensuring high quality and relevance.
• Statistical Analysis: Design and implement statistical models to understand correlations, conduct exploratory data analysis, and assess key risk factors.
• Model Development: Build, validate, and optimize IFRS 9 and decision scorecard models with a focus on predictive power, regulatory standards, and audit requirements.
• Challenger Models: Develop and compare challenger models to ensure robust decision-making frameworks.
• Insights & Recommendations: Provide actionable insights supported by analytical findings, recommending procedural and strategic improvements for banking operations.
• Client Delivery: Develop fit-for-purpose solutions aligned with client objectives and strict timelines.
• Stakeholder Communication: Create compelling presentations tailored to senior stakeholders and regulatory teams.

Required Skills & Expertise:

• Technical Proficiency: Advanced knowledge of statistical modeling techniques (e.g., Linear/Logistic Regression, Decision Trees) and tools like SAS, Python, or R.
• IFRS 9 Expertise: Hands-on experience in PD, LGD, EAD modeling, macroeconomic modeling, impairment calculations, SICR assessments, and back-testing.
• Scorecard Development: Proven experience in building acquisition, behavioral, and collection scorecards.
• Domain Knowledge: Familiarity with collections and recoveries platforms (e.g., Debt Manager) is an advantage.
• Communication: Strong ability to convey complex concepts clearly to diverse audiences.

Candidate Profile:

• Educational Background: Master’s in Statistics, Economics, Operational Research, or Engineering; Bachelor’s degree with relevant experience will also be considered.
• Professional Experience: Prior experience working with a bank or in a banking analytics role within a third-party consultancy is highly desirable