Job
Description
About this role: Wells Fargo is seeking a Lead Quantitative Analytics Specialist. In this role, you will: Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly statistical theory Qualify monitor markets and forecast credit and operational risks Strategize short and long-term objectives, and provide analytical support for a wide array of business initiatives Utilize stochastic, structured securities, spread analysis, with the expertise in the theory and mathematics behind the analysis Review and assess models inclusive of technical, audit, and market perspectives Identify structure and scope of review Enable decision making for product and marketing with broad impact and act as key participant to develop and document analytical models Collaborate and consult with regulators and auditors Present results of analysis and strategies Required Qualifications: 5+ 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: A Senior Quantitative Analytics Specialist should have a deep academic knowledge, broad based approach to solve business problems. He/she should approach the problem agnostic of analytic technique, tool or process. Ability to think outside the box and provide ensemble solutions should set them apart to be a high performing team member. 4+ years of experience with minimum Masters/ Phd in a quantitative field such as applied math, statistics, engineering, physics, or mathematical finance. Performing mathematical model validation using Python, C++, R, and SQL or other programming languages and mathematical/statistical packages Producing required documentation to substantiate model validation Analyzing processes and work flows to make recommendations for process improvement in various risk management and/or business areas as well as participating in and leading model risk projects. Strong mathematical, statistical, analytical and computational skills Strong communication skills for a variety of audiences (other technical staff, senior management and regulators) both verbally and in writing Capability to multi-task and finish work within strict timelines and provide timely requests for information and follow-up questions Ability to work independently on complex model validations from start to finish Able to demonstrate first-hand knowledge of advanced topics in various mathematical and numerical methods such as Monte Carlo, stochastic calculus, differential equations, linear algebra, applied probability, and statistics; 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 Attention to detail in both analytics and documentation Aptitude for synthesizing data to 'form a story' and align information to contrast/compare to industry perspective Intellectually curious, who enjoy solving problems Excellent programing skills and use of software packages such as C++, Python, R, SAS and SQL Ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment Good interpersonal skills and ability to develop partnerships and collaborate with other business and functional areas.
