Wells Fargo Bank N.A. seeks a Senior Quantitative Analytics Specialist in San Francisco, CA.

Job Role and Responsibility: Design, develop, and deploy financial models using state of the art techniques available in the open stack and/or vendor solutions. Create interactive finance visualization tools and dashboards. Build a highly scalable framework for ingesting, transforming and enhancing finance data at web scale. Partner with line of business executives and senior leaders to frame the problem and define/identify business objectives. Identify/assess financial data sources. Conduct comprehensive literature reviews to support the methodology decisions you will make as part of financial model development. Design and build effective data visualizations. Communicate the results to the line of business. Write comprehensive and accurate finance model development documentation. Develop a model monitoring plan. Knowledge of financial regulatory requirements related to model risk management (FRB/OCC SR 11-7). Adhere to corporate model risk policy and ensure compliance with model risk management. Working with other data science teams to identify, gather, retain, and publicize modeling artifacts required for approved and repeatable processes. Contribute to data science team’s group effort to stay concurrent with the cutting-edge algorithms methodologies in the open source community and vendor solutions. Work with technology and production teams to operationalize financial models. May be called upon to review vendor models and solutions and/or financial models developed outside of the Center of Excellence (COE). Telecommuting is permitted up to 2 days a week. Position must appear in person to the location listed as the work address.

Travel required: None

Required Qualifications: Master’s degree in Management Sciences and Quantitative Methods, Statistics, Mathematics, or related quantitative discipline plus 4 years of experience in the job offered or in a related quantitative analytics role. 

Specific skills required:

• Data transformation and data wrangling experience, using tools such as SQL;

• Experience with model development using statistical modeling and machine learning techniques;

• Proficiency in programming languages Python, Java, Scala, or R;

• Solid understanding of machine learning techniques including neural networks, RandomForest, GBM and SVM;

• Solid understanding of statistical modeling techniques including time series forecasting, linear regression, logistic regression, panel data analysis;

• Exposure to big data tools Spark, Hive, Kafka, and Map Reduce;

• Experience with machine learning libraries MLlib, scikit-learn, H2O; and

• Experience with cloud platforms GCP, AWS, and Azure.

Salary: $167,000 - $260,000

Pay Range

Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.

Posting End Date:

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