Senior Quantitative Analytics Specialist (Req. #000233)

at  Wells Fargo

At Wells Fargo, we want to satisfy our customers’ financial needs and help them succeed financially. We’re looking for talented people who will put our customers at the center of everything we do. Join our diverse and inclusive team where you’ll feel valued and inspired to contribute your unique skills and experience.
Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.
Corporate Risk helps all Wells Fargo businesses identify and manage risk. The team focuses on several key risk types, including conduct, credit, financial crimes, information security, interest rate, liquidity, market, model, operational, regulatory compliance, reputation, strategic, and technology risk.
The group provides leadership, enhances communications, assists with problem identification and solutions, and shares best practices. In addition, the group provides an enterprise-wide view of risk, assists management and our Board of Directors in identifying and monitoring risks that may affect multiple lines of business, and takes appropriate action when business activities exceed the risk tolerance of the company.
Wells Fargo Bank N.A. seeks a Senior Quantitative Analytics Specialist in Charlotte, North Carolina.
Job Role and Responsibility: Develop, implement, calibrate and validate various models and statistical techniques like logistic regression, time series analysis, multivariate statistical analysis, Random forest, GBM or XGBOOST etc. Engage with business partners, SMEs and other stakeholders effectively for performing problem formulation, establishing data quality requirements, preparing solution design, identifying data sources for developing model training, scoring and operationalization data pipelines as well as conducting data transformation validation during the model development lifecycle. Follow AGILE methodology in the model development process. Create reusable code components. Establish a consistent and collaborative cross functional framework with other analytic teams throughout the enterprise like data engineering and technology solutions partners who understand the complexities of building data products, operating as true thought partners and proactively driving conversations from a data-informed perspective to build AI solutions. Own the internal stakeholder relationship with all delivery partners. Offer technical coaching to junior team members and apprentices as and when required. Prepare detailed model development documentation for ensuring model adherence to corporate model risk management and compliance with regulatory and internal audit requirements. Define KPIs to monitor the health and accuracy of the model in production. Help the business as a technical advisor in the development of a model monitoring plan document to ensure the stability and robustness of the model and its results. 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:

Position requires a Master’s degree in Statistics, Mathematics, Physics, Engineering, or related quantitative field and two (2) years of experience in the job offered or in a related quantitative analytics role.

Specific skills required:

• Programming languages used for statistical analysis and data programming including but not limited to Python, R, SAS, SQL, C++
• Predictive Modeling experience using machine learning tools - Scikit-learn, MLlib, H2O/GCP
• Modeling, Optimization, Simulation, Computational Statistics and Machine learning concepts
• Data wrangling and transformation experience with big data tools - PySpark, SQL, Teradata, and Hadoop

APPLICANTS WITH DISABILITIES

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .

WELLS FARGO RECRUITMENT AND HIRING REQUIREMENTS:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process

Please refer the Job description for details