Quantitative Analytics Senior Manager

About this role:

Wells Fargo is seeking a Quantitative Analytics Senior Manager to lead the Decision Science and Artificial Intelligence model risk team within Model Risk Management (MRM).

Model Risk Management (MRM): Model Risk Managementis the second line of defense and is responsible for validating models, independently overseeing the management of model risk exposures across the enterprise, including governing, monitoring, and reporting on aggregate model risk exposures, model validations, and model oversight. This oversight extends to all phases of a models life cycle, including model identification, development, validation, implementation, resolution of model risk findings, model usage, performance monitoring, documentation, and retirement.

The Decision Science and Artificial Intelligence (DSAI) team: this team oversees model risk in financial crimes, fair lending, marketing, fraud detection, credit scoring, natural language processing (NLP) and generative AI. The responsibilities of the DSAI Group include an end-to-end responsibility of managing the model risk over the model lifecycle including risk tiering, validation, and performance monitoring, etc.

In this role, you will:

• Manage and develop teams responsible for the creation, implementation of complex financial and statistical models
• Analyze and manage risks to forecast losses or enable decision making for business, product, marketing, or other functional areas
• Support financial products, portfolios, business process and risk management
• Perform various compliance with corporate and regulatory reporting, involving finance and capitalization requirements
• Determine scope and prioritization of work
• Perform key input in the development of strategy, policies, procedures, and organizational controls
• Manage one or more teams of highly skilled quantitative analysts or managers
• Interface with internal and external audit or regulators
• Manage allocation of people and financial resources for Quantitative Analytics
• Develop and guide a culture of talent development to meet business objectives and strategy

Required Qualifications:

• 6+ years of Quantitative Analytical experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 3+ years of management or leadership experience
• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Desired Qualifications

• Knowledge of regulatory requirements: SR 11-7, industry standards on model validation, model governance, extensive expertise and keen insight on the model risk management process and future directions, expertise in defining model performance metrics and risk reduction techniques.
• Master's degree or higher in statistics, economics, computer science, optimization, electrical engineering, or a related quantitative discipline
• Previous model development or validation experiences for at least two areas of marketing, fraud detection, credit scoring, and generative AI.
• In-depth knowledge of AI/ML methodologies such as ensemble algorithms, neural networks, supervised and unsupervised learning.
• Strong computing and programming background and knowledge of one or more languages such as Python
• Experience with ML/AI computing platforms and tools
• Excellent oral, written, and interpersonal communication skills, with an ability to communicate effectively to audiences of varying technical maturity.

Job Expectations:

• Manage a team of highly experienced model risk professionals, both individual contributors and managers, and deliver on the teams book of work.
• Be responsible for model risk management, including model validation, performance monitoring and governance for a suite of models covering marketing, fraud detection, credit scoring, natural language processing (NLP) and generative AI.
• Examine and disseminate best practices across validation teams to drive continuous improvement in model validation quality, processes, procedures, validation libraries, technical infrastructure, standards, and automation.
• Proactively identify efficiency opportunities and execute strategic initiatives in collaboration with peer teams.
• Formulate structures and processes to help validation teams to transition from a validation centric role to a model risk management centric function.
• Stakeholder management: engage both internal (developers, risk managers, auditors) and external (regulators) stakeholders to communicate model validation process and standards.
• Identify and work to reduce model risk according to Banks model risk policies and standards.
• Proactively manage talent within the team and contribute to managing the broader talent landscape of quantitative roles across the bank.
• Bring thought leadership to the MRM group and to the broader quant community in the bank.