Lead Quantitative Analytics Specialist

About the role

The Retail Investing and Financial Advice Modeling (RIFAM) team at Wells Fargo seeks a Lead Quantitative Analytics Specialist to advance modeling capabilities for the Securities Based Lending business within Wealth and Investment Management. The role involves developing, validating, and governing quantitative models for risk measurement and margin setting across diverse financial products. This position is based in Bengaluru, India, as an on-site full-time opportunity.

What you’ll do

• Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly statistical theory
• Monitor markets and forecast credit and operational risks
• Strategize short and long-term objectives and provide analytical support for business initiatives
• Utilize stochastic, structured securities, and spread analysis with expertise in underlying theory and mathematics
• Review and assess models from technical, audit, and market perspectives
• Enable decision making for product and marketing by developing and documenting analytical models
• Collaborate and consult with regulators and auditors
• Present results of analysis and strategies to stakeholders

What you’ll bring

• 5+ years of Quantitative Analytics experience or equivalent combination of work, training, military experience, or education
• Bachelor's degree or higher in mathematics, statistics, engineering, physics, economics, or computer science
• Proficiency in Python, SQL, and GitHub programming skills

Nice to have

• PhD degree in a quantitative discipline
• Model development and implementation experience in the Financial Services industry
• Strong expertise in Securities Based Lending (SBL) modeling including VaR, Expected Shortfall, stress testing, and scenario analysis
• Solid understanding of securities-based lending business, collateral risk management, and lending portfolio analytics
• Deep experience modeling equities, fixed income, structured products, pooled investments, floating-rate instruments, ESOPs, IPOs, and digital asset-related products
• Solid understanding of statistics and time series analysis
• Experience with model review, validation, and lifecycle activities within a large financial institution
• Working experience developing or benchmarking models in Python

Skills

Education

Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science