Risk Manager II (US)

TD Bank • Southfield, MI

3d

About The Position

The Risk Manager II manages the creation, implementation, and validation of risk segmentation strategies, including adjudication, exposure management, risk segmentation, and financial return optimization. The role calls for a strong statistical and mathematical background and auto lending experience, with expertise in statistical modeling, scorecard development, loss prediction, and machine learning. It also requires hands-on analytics experience with bureau and alternative data, feature engineering, and attribute aggregation, along with advanced proficiency in SAS, R, Python, and related analytical tools.

The position integrates large and diverse datasets, develops and enhances scorecards and models across the credit life cycle, and coordinates model deployment across FICO Decision Engine, Python, and related platforms. It partners with stakeholders on Model Risk Management due diligence and issue resolution, uses statistical models and vendor data platforms to improve acquisition and portfolio performance, and supports downstream model use. The role also consolidates business impact analyses for model or strategy changes and communicates findings to management.

At the enterprise or group business level, the role acts as a primary regulatory interface on risk issues and requirements for a key business segment, assesses existing and new regulations, and provides direction. It works cross-functionally beyond Risk, represents the business on corporate initiatives, identifies key risks and implications, and provides direction in complex situations. The position performs functions noted for Risk Manager I.

The role is based in Southfield, Michigan. The stated work schedule is 40 hours. Domestic travel is occasional; international travel is never. The position involves continuous sedentary work, multitasking, operation of standard office equipment, prolonged concentration, and reading, writing, and comprehending instructions. Other occasional physical activities are described in the posting.

Requirements

• Bachelor's degree required.
• 10+ years of experience required.
• Strong statistical and mathematical background with auto lending experience.
• Expertise in logistic regression, decision trees, clustering, survival analysis, GLM, gradient boosting, scorecard development, reject inference, PD/LGD loss prediction, and machine learning.
• Hands-on analytics experience with bureau and alternative data sources, including knowledge of feature engineering and attribute aggregation.
• Advanced proficiency in SAS, R, Python, and related analytical tools.
• Proficient PC skills in MS Office and a variety of PC-based analytical and reporting software packages.
• Experience with relational databases and ETL using common languages such as SQL or SAS.
• Strong analytical and problem-solving skills to interpret data and draw conclusions.
• Flexibility to adapt to rapidly changing requirements.
• Extremely strong attention to detail, with the ability to manage a range of tasks and prioritize.
• Proven ability to develop and maintain productive business and peer relationships.
• Excellent written and verbal communication skills.
• Experience developing and presenting recommendations to Senior Management.

Nice To Haves

• Graduate degree preferred.
• Working knowledge of SAS Enterprise Miner, FICO Model Builder, or Angoss Knowledge Seeker.
• Progressive work experience in addition to the stated experience may be considered.

Responsibilities

• Manage the creation, implementation, and validation of risk segmentation strategies, including adjudication, exposure management, risk segmentation, and financial return optimization.
• Integrate large, diverse datasets, apply feature engineering, and identify trends and patterns to support model development and enhancement.
• Develop and enhance scorecards and models throughout the credit life cycle using statistical methodologies and machine learning techniques.
• Coordinate model deployment across FICO Decision Engine, Python, and related platforms.
• Partner with stakeholders on Model Risk Management due diligence and timely issue resolution.
• Use statistical models and vendor data platforms to improve acquisition and portfolio performance.
• Support downstream model use, consolidate business impact analyses related to model or strategy changes, and communicate key findings to management.
• Act as a primary regulatory interface on risk issues and requirements for a key business segment; assess existing and new regulations and provide direction.
• Work cross-functionally with teams beyond Risk and represent the business on corporate initiatives.
• Identify key risks and implications and provide direction in complex situations.

Benefits

• Health and well-being benefits
• Savings and retirement programs
• Paid time off, including Vacation PTO, Flex PTO, and Holiday PTO
• Banking benefits and discounts
• Career development
• Reward and recognition
• Training programs
• Online learning platform and mentoring programs
• Variable compensation and incentive awards, including potential cash and/or equity awards

What This Job Offers

• Job Type: Full-time
• Career Level: Senior