Quantitative Manager-CCAR​/CECL

Quantitative Manager – CCAR/CECL

Location:

Virtual, Ohio 00000.

The Quantitative Manager will lead and support the model governance analytical framework development, model implementation, monitoring, and documentation of quantitative models used in commercial/wholesale credit risk rating, including PD, LGD, and EAD 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 related economics.

Qualified candidates should have proven project management skills, outstanding modeling and quantitative analytics background, and strong communication skills. The candidate must be able to multi‑task effectively and remain results‑oriented. The desirable candidate will operate with a high degree of independence while working effectively in a collaborative environment. Responsibilities include building data and analytical infrastructure foundations, refining processes, developing analytical intelligence and dashboard reporting, building analytical solutions, informing business decisions, and managing projects aimed at improving efficiency and 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.

• Provide quantitative analytical support for commercial credit risk and modeling, overseeing the full lifecycle process of development, implementation, and monitoring of quantitative models for commercial credit risk rating and portfolio management, including PD, LGD, and EAD models, with a focus on measurement metrics and monitoring methodology framework development.
• Provide analytical consulting support to LOB teams and other cross‑functional business partners for ad‑hoc business analytics requests and formulate analytical procedures to deliver actionable insights and analytical solutions.
• Develop and continuously support and enhance data reconciliation infrastructures and data construction foundational processes to ensure data quality and achieve process efficiency for model development, monitoring, and business decisions.
• Prepare standard model and monitoring documentation that aligns with regulatory expectations and internal governance standards.

• Advanced degree in quantitative analytics, statistics, economics, engineering, or a related field.
• 8–10 years of experience in statistical/econometric modeling, data analytics, and analytical reporting.
• Proficiency in programming languages and tools such as Python, SAS, SQL, and VBA.
• Experience with complex data systems, extracting and constructing datasets, and using cloud‑based tools such as Snowflake.
• Good understanding of credit risk modeling frameworks, scorecard development, and portfolio management concepts.
• Strong verbal and written communication skills and ability to effectively present technical materials clearly to both technical and non‑technical audiences.
• Strong analytical agility and problem‑solving skills.
• Ability to work collaboratively in cross‑functional teams and manage multiple priorities.
• Familiarity with commercial lending products and regulatory requirements is a plus.

Total Base Pay Range: 96,500 – 207,500 USD annually. The base salary for this position is reflective of the range of salary levels for all roles within this pay grade across the U.S. Individual salaries within this range will vary based on factors such as role, relevant skillset, relevant experience, education, and geographic location. In addition to the base salary, this role is eligible to participate in an incentive compensation plan based on company, line of business, and/or individual performance.

Fifth Third Bank, National Association is proud to have an engaged and inclusive culture and to promote and ensure equal employment opportunity in all employment decisions regardless of race, color, gender, national origin, religion, age, disability, sexual orientation, gender identity, military status, veteran status or any other legally protected status.