Wells Fargo Bank N.A. seeks a Quantitative Analytics Specialist in Charlotte, NC.

Job Role and Responsibility:

Develop, implement, and calibrate various analytical models. Perform highly complex activities related to financial products, business analysis and modeling. Perform basic statistical and mathematical models using Python, R, SAS, C++ and SQL. Perform analytical support and provide insights regarding a wide array of business initiatives. Provide solutions to business needs and analyze workflow processes to make recommendations for process improvement in risk management. Collaborate and consult with peers, colleagues, managers, and regulators to resolve issues and achieve goals. Telecommuting is permitted up to 2 days per week. Position must appear in person to the location listed as the work address.  

Travel required:  0%

Required Qualifications:

Position requires a Master's degree in Statistics, Mathematics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline plus 2 years of experience in the job offered or in a related quantitative analytics role. Will alternatively accept a PhD in Statistics, Mathematics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline plus 0 years of experience.

Specific skills required:

Skills can be gained through work experience or graduate level coursework. 

Experience in at least 4 of the following:

•              Programming languages used for statistical analysis and data programming including SAS, R, C++, Python, SQL, and MATLAB;

•              Analytical software Hadoop and NoSQL;

•              Linux and Unix Operating Systems;

•              Predictive modeling using statistical and machine learning techniques;

•              Stochastic Modeling, Optimization, Simulation, Computational Statistics, and Machine Learning;

•              Statistical model development/validation;

•              Documenting and presenting detailed model development and validation outcomes and results;

•              Utilizing best modeling practices and methodologies in the areas of data processing, sampling, model design/specification, model performance assessment, and evaluation testing;

•              Application of analytical, statistical and forecasting methods with focus on the theory and mathematics behind the analyses;     

•              Performing model validations and clearly documenting evidence of validation activities to identify conceptual weaknesses in a model and understand tradeoffs with alternate approaches;

•              Providing effective challenges to models developed in lines of business to reduce model risk to meet or exceed regulatory and industry standards;

•              Developing and validating a variety of statistical, machine learning and Artificial Intelligence (AI) models, including hazard models, logistic regression models, time series models, large-scale econometric models, and gradient boosting machines;

•              Working within the regulatory framework for financial institutions and interfacing with regulators and auditors.

Posting End Date:

*Job posting may come down early due to volume of applicants.