Senior Quantitative Analytics Specialist

This role supports the development, implementation, and enhancement of advanced analytical models and methodologies used to evaluate and manage credit risk. The successful candidate will leverage statistical, econometric, and machine learning techniques to deliver insights that support credit decisioning, portfolio management, and business strategy. This position offers an opportunity to collaborate with business partners, model developers, risk professionals, and auditors while working with large-scale data and innovative analytical solutions.

Responsibilities

• Perform highly complex activities related to creation, implementation, and documentation of analytical models.
• Use highly complex statistical theory to quantify, analyze, and manage credit risk.
• Participate in discussions related to analytical strategies, modeling, and forecasting methods.
• Collaborate and consult with regulators, auditors, and technically oriented individuals.

Requirements

• 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
• Master’s degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.

Qualifications

• Data analysis, modeling, and programming experience using SAS and Python or R.
• Experience contributing to and maintaining code within a collaborative team environment.
• Significant analytic experience in statistical, econometric, and machine learning approaches to data analysis and modeling.
• Experience working with relational databases and S3 or Iceberg data file systems and distributed data processing tools such as Spark.
• Theoretical and applied knowledge pertinent to building Credit Decisioning models using advanced statistical techniques/machine learning for credit decisioning and account management.
• Experience with linear models and Machine Learning techniques including time-series, OLS, logistic regression, hazard models, panel regression, gradient boosted decision trees.

Job Expectations

• This position offers a hybrid work schedule with current requirements of 3 days in-office.
• Willingness to work on-site at the stated location on the job opening.
• This position is not eligible for Visa sponsorship.
• Specific compliance policies may apply regarding outside activities or personal investing; affected employees will be expected to provide information to the Wells Fargo Personal Account Dealing Team and abide by applicable policy requirements if hired.

Locations

• Minneapolis, Minnesota
• Charlotte, North Carolina
• Irving, Texas
• Des Moines, Iowa

Pay

Minneapolis, Minnesota Pay Range: $153,000 - $239,000 USD Annual (this range may not be applicable to other locations). 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.

Benefits

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement