Senior Quantitative Analytics Specialist (Req #001942)

Wells Fargo•San Francisco, CA

1d•$167,000 - $260,000•Hybrid

About The Position

Wells Fargo Bank N.A. seeks a Senior Quantitative Analytics Specialist in San Francisco, CA. This role involves designing, developing, and deploying financial models using state-of-the-art techniques, creating interactive finance visualization tools and dashboards, and building a scalable framework for finance data ingestion and transformation. The specialist will partner with business executives to define objectives, identify data sources, conduct literature reviews for methodology decisions, and design effective data visualizations. Communication of results, comprehensive documentation of model development, and development of model monitoring plans are key responsibilities. Knowledge of financial regulatory requirements related to model risk management (FRB/OCC SR 11-7) and adherence to corporate model risk policy are essential. The role also includes collaborating with other data science teams to manage modeling artifacts, staying current with cutting-edge algorithms, and working with technology teams to operationalize financial models. Review of vendor models and external financial models may also be required. Telecommuting is permitted up to 2 days a week, but the position requires in-person presence at the work address.

Requirements

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.
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;
Experience with cloud platforms GCP, AWS, and Azure.
Knowledge of financial regulatory requirements related to model risk management (FRB/OCC SR 11-7).

Responsibilities

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.
Adhere to corporate model risk policy and ensure compliance with model risk management.
Work with technology and production teams to operationalize financial models.
Review vendor models and solutions and/or financial models developed outside of the Center of Excellence (COE).
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.