Senior Quantitative Analytics Specialist

About this role: Wells Fargo is seeking a Senior Quantitative Analytics Specialist for our DSAI(data science and Artificial intelligence) team.

• 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

• 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

• 4+ years of experience with Master's Degree or equivalent in computer science, electrical engineering, data science, or another discipline with a strong quantitative core and extensive exposure to software engineering or scientific computing
• Hands-on experience and deep knowledge in at least one of these areas: NLP and GenAI and/or Agentic models, with an exposure to model risk management policies and procedures preferably in financial domain.
• Change management skills and proven ability to conceptualize and communicate designs and plans;
• Knowledge of recent frameworks for Machine Learning, GenAI and Agentic pipelines.
• Hands-on experience with LangGraph, LangChain, Google ADK, Agentic Performance evaluation pipelines like Arize a plus.
• Deep understanding of data modeling and relational databases. Advanced SQL, including analytical functions and recent additions to the SQL standard;
• Skill in managing relationships with key model stakeholders
• Eagerness to contribute collaboratively on projects and discussions
• Perpetual interest in learning something new, but being comfortable with not knowing the all the answers
• Intellectually curious, with an attention to detail.
• Good verbal and written communication skills as well as interpersonal skills;
• Ability to prioritize work, meet deadlines, achieve goals, and work in a dynamic and complex environment; and
• Ability to develop partnerships and collaborate with other business and functional areas.

• Work at the intersection of technologies related to Data Science AI/ML, Natural Language Processing and Generative AI including Agents and Skills and their application to Fraud model development and validation. The role requires strong statistical background and expertise in Quantitative Modeling. The responsibilities include, but are not limited to, the following:
• Managing model risk throughout the model lifecycle from model identification to model retirement through various tasks including risk ranking, model validation, change management and performance monitoring etc.
• Delivering high quality technical reports ensuring factual accuracy, conceptual alignment, critical assessment and compliance to all policies and procedures.
• Helping to develop and evaluate the architecture and foundational components of internal validation tools, developing fully operational prototypes, and deploying them in partnership with our Technology partners.
• Providing guidance to the broader MRM community on best model risk management practices by leading or contributing to efficiency, effectiveness and automation efforts.