Senior Quantitative Analytics Specialist

Job Summary

Wells Fargo is seeking a Senior Quantitative Analytics Specialist.

In this role, you will:

• Perform highly complex activities related to creation, implementation, and documentation
• Use highly complex statistical theory to quantify, analyze and manage markets
• Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives
• Utilize structured securities and provide expertise on theory and mathematics behind the data
• Manage market, credit, and operational risks to forecast losses and compute capital requirements
• Participate in the discussion related to analytical strategies, modeling and forecasting methods
• Identify structure to influence global assessments, inclusive of technical, audit and market perspectives
• Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills

Required Qualifications:

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

Desired Qualifications:

• 4+ years of Risk Management experience handling liquidity risk models

Job Expectations:

• Conduct comprehensive validations of liquidity risk models, stress testing frameworks, cash flow forecasting models, and behavioral models to assess conceptual soundness, methodology, implementation accuracy, and fitness for purpose.
• Critically evaluate key model assumptions, data inputs, calibration approaches, and expert judgments related to deposit behaviors, loan commitments, and assumptions.
• Ensure liquidity models and methodologies comply with internal model risk management standards and applicable regulatory requirements, including LCR, NSFR, Resolution Liquidity Adequacy and Positioning (RLAP), and liquidity stress testing expectations.
• Assess model design, implementation, validation findings, and associated risks, providing clear recommendations for remediation and presenting validation outcomes to senior management, model owners, and governance committees.
• Maintain robust validation documentation, oversee model performance monitoring and ongoing validation activities, and contribute to model governance processes, approvals, periodic reviews, and regulatory examinations
• Experience in handling time series, logit or COX proportional hazard models and familiarity with other quant modelling techniques
• Partnering effectively with stakeholders and ensuring timely delivery of quality work.