Senior Quantitative Analytics Specialist

Overview

Senior Quantitative Analytics Specialist at Wells Fargo, focused on creating, implementing and documenting complex statistical and quantitative models for market, credit and operational risk, including forecasting losses and computing capital requirements.

What you'll do

• 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 the 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 technically oriented individuals.
• Develop regulatory credit risk models (including CCAR, CECL and IFRS), RRP valuation, and PPNR models for the commercial portfolio in SAS/Python.
• Work closely with team members to understand and enhance the data and modeling process behind existing models, develop new models, and address data and model issues/findings.
• Conduct underlying portfolio data research and analytics using strong programming skills.
• Adhere to audit and model validation governance to ensure data and modeling processes are compliant with policy and working as intended, and address model validation and regulatory feedback issues.
• Support ad-hoc analytic projects.

What you'll need

• 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of: 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.
• 4+ years of predictive modeling experience.
• Good understanding of model development and model testing.
• Proficient in statistical analysis.
• Good problem solving and analytical skills.
• 2+ 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 able to navigate a quickly changing and high demand environment while balancing multiple priorities.
• Understanding of bank regulatory data sets and other industry data sources.
• Exposure to the banking domain with strong functional knowledge in the Credit Risk area on Retail/Commercial portfolios.

Nice to have

• Experience in development of regulatory models (including CCAR, CECL and IFRS), RRP valuation, and PPNR models for the 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.

Details

• Location: Bengaluru, India.
• Posting end date: 6 Nov 2026.