Job
Description
About this role: Wells Fargo is seeking a Senior Quantitative Model Solutions Specialist In this role, you will: Lead or participate in moderately complex model maintenance and optimization initiatives related to operating processes, controls, reporting, testing, implementation, and documentation Review and analyze moderately complex data sets, quantitative models, and model outputs to validate model efficiency and results in support of business initiatives Advise and guide team on moderately complex model optimization and processes strategies Independently resolve moderately complex issues and lead team to meet project deliverables while leveraging solid understanding of policies and compliance requirements Collaborate and consult with peers, colleagues, and managers to resolve issues and achieve goals. Required Qualifications: 4+ years of quantitative solutions engineering, model solutions or quantitative model operations experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education. Desired Qualifications: Overall experience around 4 to 10 years in similar role Bachelors degree or higher in a quantitative field such as Computer Science, Applied mathematics, engineering, statistics, finance or econometrics from top tier institutes Strong problem solving skills 4+ years of experience in credit risk analytics with exposure to statistical and machine learning model development, implementation or ML Ops 4+ years Data engineer- Oracle, Teradata, Hadoop, SQL 2+ years of advanced programming expertise in SAS 4+ years of advanced programming and debugging skills in Python OOP, packaging, build and deployment, data structures and algorithms, decorators, logging, exception handling, JIT compilers 2+ years of experience in High performance computing, Big Data and real time solutions PySpark, MapR streaming, parallel processing, real time optimization. 2+ years of experience in unit testing, UAT testing, regression testing and code review Comfortable with Git, GitHub, CI/CD pipelines and UNIX commands Excellent verbal, written, and interpersonal communication skills Strong ability to develop partnerships and collaborate with other business and functional areas Knowledge and understanding of issues or change management processes Experience determining root cause analysis Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities Understanding of bank regulatory data sets and other industry data sources Ability to research and report on a variety of issues using problem solving skills Exposure to banking domain in Credit Risk area on Retail/Commercial portfolio Perform various complex activities related to predictive modeling process enhancements and Python conversions Provide engineering and analytical solutions across model development, implementation, monitoring and production in a Big Data environment Support implementation of python based solutions for real time and/or batch based Machine Learning scorecard models for consumer and commercial banking Identify opportunities and deliver process improvements, standardization, rationalization and automations
