Wf
Senior Quantitative Analytics Specialist (#001806)
MINNEAPOLIS, MN · Senior
Sponsorship not specified$153k-$239kDetected 12 hours ago
PythonMachine LearningData AnalysisStatisticsComplianceForecastingLoad TestingSASCommunicationHadoop
About the role
- Wells Fargo Bank N.A. seeks a Senior Quantitative Analytics Specialist in Minneapolis, MN.
- Utilize structured securities and provide expertise on theory and mathematics behind the data.
- Participate in the discussion related to analytical strategies, modeling and forecasting methods.
Responsibilities
- Perform highly complex activities related to creation, implementation and documentation.
- Use highly complex statistical theory to quantify, analyze and manage markets.
- Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills.
- Help us build a better Wells Fargo.
- Manage market, credit, and operational risks to forecast losses and compute capital requirements.
- Drug and Alcohol Policy Wells Fargo maintains a drug free workplace.
- Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company.
- Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
Requirements
- Degree required: Master's degree in Statistics, Mathematics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline.
- Alternative degree required: PhD in Statistics, Mathematics, Physics, Engineering, Computer Science, Economics, or related quantitative discipline.
- Amount and type of experience required: 4 years of experience in the job offered or in a related quantitative analytics role.
- Alternative experience required: 1 year of experience in the job offered or in a related quantitative analytics role.
- Specific skills required: Specific skills required: · Data analysis, modeling, and programming experience using SAS and Python or R
- Experience working with relational databases and Hadoop data file systems
- Experience with linear model technique including time-series, OLS, logistic regression, hazard models, and panel regression.
- 4 years of experience in the job offered or in a related quantitative analytics role.
Compensation
- $153,000 - $239,000 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. $0.00 - $0.00 Benefits Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below.
Benefits
- Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.
Company info
- WFC) is a leading financial services company that has approximately $2.1 trillion in assets.
- 33 on Fortune's 2025 rankings of America's largest corporations.
- News, insights, and perspectives from Wells Fargo are also available at Wells Fargo Stories.
- We provide a diversified set of banking, investment and mortgage products and services, as well as consumer and commercial finance, through our four reportable operating segments: Consumer Banking and Lending, Commercial Banking, Corporate and Investment Banking, and Wealth & Investment Management.
- Wells Fargo ranked No.
- 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.
Equal opportunity
- We Value Equal Opportunity Wells Fargo is an equal opportunity employer.
- Applicants with Disabilities To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
This listing is sourced directly from Wf's careers page and normalized into a canonical job model.