Wells Fargo Quantitative Model Solutions Specialist 

India, Telangana, Hyderabad 

459886935

In this role, you will:

• Perform various complex activities related to predictive modeling. Provide analytical support for developing, evaluating, implementing, monitoring and executing credit and PPNR models across retail secured business verticals
• Analyze data sets, quantitative models, and model output to validate model performance and results in support of business opportunities
• Develop, implement, execute and monitor credit ACL, CECL, IFRS9, Basel and CCAR models for Retail Secured portfolio
• Develop dynamic dashboards; analyze key risk parameters to help understand changes in business and model performance
• Identify opportunities for strategic and infrastructure projects. Design and deliver process improvements, standardization, rationalization and automations. Enhance and standardize performance analysis, reporting packages and business loss forecast processes
• Develop frameworks for documentation of development, implementation and monitoring processes across the team with focus on standardization of controls

Required Qualifications:

• 2+ years of quantitative model solutions or quantitative model operations experience, or equivalent demonstrated through one or a combination of the following: work experience, training, education
• 2+ years of advanced programming expertise in Python, Tableau and SAS
• Strong technical skills and problem solving skills

Desired Qualifications:

• Excellent verbal, written, and interpersonal communication skills
• Strong ability to develop partnerships and collaborate with other business and functional areas
• Knowledge and understanding of issues or change management processes
• Experience determining root cause analysis
• Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities

1 Apr 2025

Wells Fargo Recruitment and Hiring Requirements:

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.