Quantitative Manager-Credit Risk

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The Quantitative Manager will lead and support the development, implementation, and oversight of quantitative models used in commercial credit risk rating, including PD, LGD, EAD, and Commercial Risk Rating/Scorecard models. This role requires a high level of technical expertise in data analysis, statistical modeling, and business analytics, along with a strong understanding of banking products, commercial portfolio and economics.

The incumbent will operate with a high degree of independence and is recognized internally and externally as a reliable and knowledgeable resource. Responsibilities include driving business plans, refining processes, and managing projects aimed at improving efficiency and model performance.

This role is accountable for managing risk by adhering to policies and procedures, elevating concerns, and ensuring actions align with the Bank's risk appetite and commitment to a positive customer and stakeholder experience.

• Lead the development, enhancement, and validation of quantitative models for commercial credit risk, including PD, LGD, EAD, and internal risk ratings.

• Provide technical support across Risk and Finance divisions, including data sourcing, model implementation, and performance monitoring.

• Collaborate with business lines to understand analytical needs and deliver actionable insights.

• Conduct back-testing and performance analysis to ensure model accuracy and regulatory compliance.

• Respond to ad-hoc requests and support business-driven analytics initiatives.

• Document model development and ensure alignment with regulatory expectations and internal governance standards.

• Serve as a technical expert and lead a specific product, process, or projects within the infrastructure area.

• Acts as a key advisor on significant business and product decisions.

• Advanced degree in quantitative analytics, statistics, economics, engineering, or a related field.

• 8-10 years of experience in statistical/econometric modeling, data analytics, and database management.

• Proficiency in programming languages and tools such as Python, SAS, SQL, VBA, and Business Objects.

• Strong understanding of credit risk modeling frameworks, including Basel II, scorecard development, and portfolio management concepts.

• Excellent verbal and written communication skills, with the ability to present complex concepts clearly.

• Strong analytical and problem-solving skills.

• Ability to work collaboratively in cross-functional teams and manage multiple priorities.

• Experience with Microsoft Office Suite (Word, Excel, PowerPoint, Outlook).

• Familiarity with commercial lending products and regulatory requirements is a plus.

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