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

Job Role and Responsibility:

Participate in less complex initiatives and identify opportunities for process improvements within Securities Quantitative Analytics. Develop automated trading algorithms or create cutting-edge derivative pricing models and empirical models to provide insight into market behavior. Combine mathematical programming and market expertise to build and generate systematic strategies. Review and analyze basic business, operational, or technical assignments or challenges that require evaluation, and a selection of alternatives. Exercise independent judgment to guide medium risk deliverables. Use quantitative and technological techniques to solve complex business problems. Conduct research on trading cost models, liquidity models, risk models, portfolio construction methodology, and signal generation. Present recommendations for resolving more complex situations. Exercise independent judgment while developing expertise in the Securities Quantitative Analytics. Collaborate and consult with colleagues, internal partners, and stakeholders. Play an integral role to the trading floor.

Travel required:  0%

Required Qualifications:

Degree required: PhD in Statistics, Mathematics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline.

Amount and type of experience required: 2 years of experience in the job offered or in a related securities quantitative analytics role.  

Specific skills required:

· Stochastic Modeling, Optimization, Simulation, Computational Statistics; · Developing and validating a variety of statistical models including sampling and subsampling methodologies, logistic regression models, time series models, large-scale econometric models, and machine learning models including gradient boost and neural networks; · Conducting advanced time-series analysis on large-scale data and developing models for outlier detection and missing-data imputation; · Experience handling large, complex datasets, and database experience including data querying, processing, and analysis; · Strong quantitative finance skills and understanding of structured products including asset-backed securities and mortgage-backed securities; · Experience with market risk models, including Value-at-Risk (VaR), expected shortfall (ES) and related risk metrics; · Programming languages used for statistical analysis and data programming including SAS, R, C++, Python, SQL, and MATLAB; · Utilizing best modeling practices and methodologies in the areas of data processing, sampling, model design/specification, model performance assessment, and evaluation testing; · Ability to clearly document the development outcomes. Performing model validations and documenting evidence of validation activities to identify conceptual weaknesses in a model and understand tradeoffs with alternate approaches.

Posting End Date:

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