Job Description

About this role: Wells Fargo is seeking a Senior Quantitative Analytics Specialist. In this role, you will: 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 Required Qualifications: 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. Desired Qualifications: Experience in at least few of the listed domains - CCAR Stress testing, CECL, IFRS9, RRP, FCM, Basel Models, SR 15-18 and SR 11-7 guidelines First-hand knowledge of advanced topics in various mathematical and numerical methods such as Monte Carlo, differential equations, linear algebra, applied probability, and statistics Excellent command over supervised, unsupervised and semi-supervised techniques (e.g., Ensemble methods; Boosting algorithms; Statistical models like OLS, Logistic, Ridge, Lasso; Time-series techniques like ARIMAX, Error correction models, ARCH, GARCH) Excellent programing skills in Python, SQL and basic use of SAS. Job Expectations: Support model development activities, including but not limited to data analytics, segmentation, model estimation, testing and documentation for retail unsecured loss forecasting and PPNR models covering both revolving as well as close-ended products (e.g., cards, term loans, lines etc.) Use statistical modelling theories and business knowledge to assess risk, quantify losses and support computation of capital requirements Write efficient codes related to modelling processes including but not limited to data cleaning, analytics, model estimation, and scoring Support model validation and audit exams Collaborate and consult with senior business leaders and modelling managers to help deliver effective and efficient modelling solutions