About the role

Senior Lead Python Securities Quantitative Analytics Specialist at Wells Fargo developing ALM models and enhancing quantitative risk metrics. Collaborating with business stakeholders and ensuring model deployment in production environments.

Responsibilities

Develop and enhance quantitative models to measure key ALM metrics—including Net Interest Income (NII), interest rate risk, liquidity risk, and related enterprise risk indicators.
Perform forecasting and margin analysis, generating insights on net interest margin (NIM) dynamics across scenarios, portfolios, and economic environments.
Integrate pricing and risk analytics by collaborating closely with partner quant teams to ensure ALM models incorporate consistent assumptions, methodologies, and valuation frameworks.
Implement production‑ready models within an industrial‑strength analytics library, ensuring robustness, scalability, and adherence to development and governance standards.
Partner effectively with business stakeholders, quantitative teams, technology groups, and project managers to ensure successful deployment and ongoing support of ALM models in production environments.
Continuously assess and improve model development processes, identifying opportunities for efficiency, transparency, and methodological enhancements.

7+ years of Securities Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
3+ years of Python 3 experience
A master's degree or PhD in a quantitative discipline
3+ years of hands-on coding experience, Python 3 is most relevant
3+ years of product and market experience in various asset classes: rates, foreign exchange, credit, and mortgages, and structured products
3+ years of quantitative analytics development and support experience in a buy-side or sell-side institution or a quant solution vendor
Expert working knowledge in ALM framework and concepts
Experience using ALM systems (QRM, Polypaths, etc)
Experience with numerical and scientific computing libraries such as NumPy, pandas, SciPy, and PyTorch or TensorFlow
Excellent analytical, interpersonal, oral and written communication skills with a strong attention to detail across multiple audiences (Technology, Quants, Senior Management)
Ability to work through business challenges consistently, effectively, with a sense of urgency through collaboration, transparency, and leading to results
Experience in or passionate about Machine Learning and Agentic AI.