Quantitative Analytics Specialist

Wells Fargo is seeking a Quantitative Analytics Specialist.

• 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
• 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

• 2+ 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 statistics, mathematics, physics, engineering, computer science, economics, or quantitative discipline

• 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.

• 2+ years of Predictive modeling experience. Good understanding of model development and model testing.
• Proficient in statistical analysis
• Good Problem Solving and Analytical Skills.

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

• In office expectations: 4 days a week in office
• Shift timings: 1:30 PM to 10:30 PM