Senior Quantitative Analytics Specialist

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:

• Experience in development of regulatory model (including CCAR, CECL, and IFRS), RRP Valuation, and PPNR models for Commercial portfolio
• Degree in applied mathematics, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis.

Strong Quantitative Skills:

• 4+ years of predictive modeling experience. Good understanding of model development and model testing.
• Proficient in statistical analysis
• Good problem solving and analytical skills

Programming Skills:

• 2+ years of hands-on experience in Python and SQL

Additional Requirements:

• Good written and oral communication skills
• Ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment
• Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities
• Understanding of bank regulatory data sets and other industry data sources
• Exposure to banking domain with strong functional knowledge in Credit Risk area on Retail/Commercial portfolio

Job Expectations:

• Development of regulatory Credit risk (including CCAR, CECL, and IFRS), RRP Valuation, and PPNR models for Commercial portfolio in SAS/Python
• Work closely with other team members to understand and enhance the data and modeling process behind existing models, develop new models, address data and model issues/findings
• Underlying portfolio data research and analytics using strong programming skills
• Adhere to audit and model validation governance to ensure data and modeling process are in compliance with policy and are working as intended, address model validation and regulatory feedback issues
• Support ad-hoc analytic projects