Data Science Consultant

Job Description

About this role: Wells Fargo is seeking a Data Science Consultant. In this role, you will: Participate in low to moderately complex initiatives by utilizing data-driven, advanced analytical and statistical techniques to identify trends, diagnose problems, and build actionable insights or recommendations Review and analyze business, operational, technical assignments, or challenges that require research, evaluation, and selection of alternatives to convert data into meaningful insights and recommendations Exercise independent judgment to guide medium risk business hypothesis generation Present recommendations and insights for resolving low to moderately complex business needs and problems; exercise independent judgment while developing an expertise in analytic capabilities Collaborate and consult with functional colleagues, internal partners, and stakeholders to drive recommendations and strategies based on data-driven analytical insights, trends, and patterns Conduct low to moderately complex predictive analytics to build actionable insights and recommendations Design and apply algorithms to mine large sets of structured and unstructured data from various sources Ensure data completeness, accuracy, and uniformity through cleaning and validation Interpret and analyze data, using advanced analytics modeling methods and programming, to isolate patterns that lead to recommendations to solve problems and influence business decisions and strategies Required Qualifications: 2+ years of data science 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 one or a combination of the following: reporting, analytics, or predictive modeling with at least 2 years of modelling experience or theoretical knowledge. Strong analytical skills with high attention to detail and accuracy. Model development or model monitoring experience. SAS (e.g. Enterprise Guide or Enterprise Miner or Base SAS) and/or Python or R experience. Demonstrated experience with statistical modelling techniques and AI-ML techniques. Ability to create documentation of process flows, business analysis and metadata. Experience in Financial services or knowledge of consumer/retail financial products. Knowledge and understanding of fraud detection process in banking. Dedicated, enthusiastic, self-driven and performance-oriented and capable of handling multiple projects simultaneously. Possesses a strong work ethic and thrives in a collaborative team environment. Excellent verbal, written, and interpersonal communication skills and demonstratable strong presentation skills. Engage with cross culture team members and stake holders. Experience working on BI Tools like QlikView or Tableau. Experience with MS Office Suite (PowerPoint, Excel, Word) End-to-End model monitoring of fraud models. Support annual model review and (re)validation efforts. Support model implementation, monitoring, and documentation. Provide analytical support for different types of fraud identification and prevention strategies. Perform ad-hoc analysis to understand portfolio trends and develop actionable solutions. Support analysis and development of strategies, methods, and other fraud- related projects. Establish mechanisms to manage and mitigate fraud risks for all portfolios. Mentors junior Team Members. Serve as a valuable resource to the other members of the team while promoting knowledge sharing and team collaboration.