Job Description

Lead Quantitative Analytics Specialist - (ALM Modeling , Balance sheet modeling, IRRBB,EVE,FTP, Deposit models, Liquidity Risk models) About this role: Wells Fargo is seeking a Lead Quantitative Analytics Specialist. Corporate Risk helps Wells Fargo businesses identify and manage risk. The team focuses on three key risk areas: credit risk, operational risk and market risk. As the company's second line of defense, Corporate Risk or Independent Risk Management provides independent oversight of risk-taking activities. Independent Risk Management establishes and maintains Wells Fargo's risk management program and provides oversight, including challenges to and independent assessment of the frontline's execution of its risk management responsibilities. Corporate Risk roles depend on a variety of skills, viz. data analysis and synthesis, root cause analysis, change management, process management & execution, risk governance, risk strategy, risk identification & assessment, risk prevention, controls & mitigation, risk monitoring, reporting & escalation, risk systems & technology. In this role, you will: Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly statistical theory Qualify monitor markets and forecast credit and operational risks Strategize short and long-term objectives, and provide analytical support for a wide array of business initiatives Utilize stochastic, structured securities, spread analysis, with the expertise in the theory and mathematics behind the analysis Review and assess models inclusive of technical, audit, and market perspectives Identify structure and scope of review Enable decision making for product and marketing with broad impact and act as key participant to develop and document analytical models Collaborate and consult with regulators and auditors Present results of analysis and strategies Required Qualifications: 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science Desired Qualifications: Risk Modeling Group (RMG) Forecasting: The team is responsible for development and delivery of models leveraged for Credit Risk, Compliance Risk, and Operational Risk. These include models for credit and pre-provision net revenue (PPNR) forecasting, and fair lending. Deposit & PPNR: This team within RMG (Risk Modeling Group) Forecasting is responsible for driving entire model life cycle (model development, monitoring & forecasting) of Wells Fargo deposit balance and yield. Deposit & PPNR team support Pre-Provision Net Revenue (PPNR) estimates including forecasting deposit balance & rate models to support ALM, FP&A, CCAR and Recovery and Resolution Planning. Team is responsible for the design, development, delivery, monitoring and forecasting of econometric forecasting models for Deposit (Interest Expense), Fees (Non-II) & Expense (Non-IE) components to support business planning and economically sensitive CCAR submission . Enhance Deposit modeling framework effectively ensuring consistency in modeling methodologies, Annual/Semi-Annual validations and Audit- tracking thereby ensuring controlled model risk Contribute to the banks balance sheet and income statement modeling methodologies in support of asset & liability management (ALM), FP&A and capital planning by capturing interest rate risk in the banking book (IRRBB) by EVE Responsible for steering stakeholder conversations of user review and model challenge sessions with Business, Finance, Treasury and Model Risk Management for signoffs on Champion & Challenger models Conduct econometric and statistical analysis of time series and panel data sets Knowledge on Python/R/SAS is must Knowledge on model life cycle (development, monitoring, implementation and forecasting) and its intricacies are good to have Should possess strong documentation capabilities which would effectively convey complex models and processes Communicate design and results of complex models to a variety of audiences, including senior management, bank supervisors, Model Governance, Internal Audit and LOB end users Coordinate with business partners, including forecasting teams, and end users to ensure accurate model usage and implementation Adhere to model validation governance to ensure models are following policy and are working as intended, address model validation and regulatory feedback issues Solving model development and model analytics/forecasting challenges in python with quick turn arounds Master's degree or higher in a quantitative field such as Statistics/Economics 5+ years of experience in Deposit & PPNR, Treasury Analytics , or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 5+ years of experience in Deposit balance sheet modeling and treasury/liquidity analytics in support of asset & liability management (ALM), FP&A and capital planning by capturing interest rate risk in the banking book (IRRBB) by EVE 5+ years of advanced programming expertise in SAS or Python or R Strong documentation and project management capabilities with ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment Excellent verbal, written, and interpersonal communication skills Strong ability to develop partnerships and collaborate with other business and functional areas Excellent verbal, written, and interpersonal communication skills Perform various complex activities related to deposit balance sheet modeling Provide analytical support for development, remediation, monitoring, and production of Deposit & PPNR models Support development, implementation, execution and monitoring of Regulatory models such as Basel, CECL, and CCAR models Develop dynamic dashboards; analyze key risk parameters to help understand changes in business and model performance Identify opportunities and deliver process improvements, standardization, rationalization and automations Enhance and standardize performance analysis, reporting packages and business loss forecast processes Maintain documentation for development, implementation and monitoring of processes across the team with focus on standardization of controls Ability to identify and manage complex issues and negotiate solutions within a geographically dispersed organization