Lead Data Scientist (III), Fraud Model Validation

Work Location:

Mount Laurel, New Jersey, United States of America

Hours:

40

Pay Details:

$141,960 - $230,880 USD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs. 

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Line of Business:

Risk Management

Job Description:

The Senior Manager, Quantitative Analytics Lead leads the advanced quantitative models' development to meet business requirements and oversees and lead a team of Quantitative Strategist professionals focused on the most complex set of pricing models.  This role is also considered an organizational expert on quantitative models in a wide range of asset classes and provides guidance to the team and others as needed.  This role provides interpretation through in-depth understanding of the models and business. This job provides forecasts and financial plans to drive business results, strategy and decisions.

The Model Validation (MV) group is a centralized Model Risk Management function within the Bank. It has seen fast growth in the past few years reflecting global regulators’ increasing attention on model risk. The Artificial Intelligence / Machine Learning (AI/ML) Model Validation team within MV is responsible for the review/vetting and approval of AI/ML models developed and used across the enterprise (e.g., Fraud, Retail Credit Risk, Marketing, NLP, TD Wealth, TD Asset Management, Treasury Balance Sheet Management, TD Insurance). By ensuring an objective and independent evaluation of models, the Model Validation function is critical to the effective measurement and management of model risk across the TD Bank Group.
The position reports to AVP, AI/ML Model Validation group. Detailed accountabilities include:
•    Lead a team of Machine Learning and Data Scientists to perform validation of all Fraud and Cyber Security models deemed in-scope by the bank-wide Model Risk Policy. 
•    Recommend the approval of models or other corrective actions based on the independent validation.
o    Lead and support a team of model validators.
o    Ensure performance objectives are set for all staff and that performance feedback is provided on a regular basis.
o    Communicate group objectives and strategies and align group activities in support of business objectives.
•    Support employee development activities, coach and support direct reports in meeting their personal development objectives.
•    Assume a leadership role in developing standards and procedures for vetting and validation Fraud and Cyber Security models that are compliant with the Bank’s internal Model Risk Policy, adhere with industry and academic best practices, and meet regulatory requirements.
•    Respond to requests from both Canadian and U.S. regulators, internal and external audit in their review/audit of models and vetting/validation process and procedures. Provide information and assistance as required.
•    Work effectively with internal Model Development groups, Audit, and other internal partners to ensure models meet required Bank standards for use.
•    Play a key role in ensuring the appropriate use of Fraud and Cyber Security models. Identify the need to implement new models/techniques as industry standards evolve and regulatory requirements change.
•    Maintain full professional knowledge of techniques and developments in the field of AI/ML, Fraud and CyberSecurity; and share knowledge with business partners and senior management. Provide subject matter expertise to business units on AI/ML Fraud and Cyber Security modeling and validation.
*Job Requirements 
•    Advanced quantitative and AI / ML skills with post-secondary degree in one or more of the following areas: Machine Learning, AI, Computer Science, Engineering, Software Engineering, Statistics, Mathematics and etc. 
•    8+ years of experience in either developing or validating Fraud / Cyber Security models; and 4+ years of experience in leading a small team of data scientists.
•    In-depth knowledge of fraud risk management and detection of different types of fraud attacks.
•    In-depth knowledge of AI / Machine Learning techniques, concepts and theory; Statistical/probability theory and applications. Understa