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The Role
Develop and implement advanced statistical, machine learning, and risk models for banking applications. Forecast losses, calculate capital requirements, analyze large datasets, validate and monitor models, and support model deployment. Partner with business, technology, regulators, and auditors while documenting model lifecycle activities. The role requires expertise in Python, PySpark, SQL, statistical analysis, machine learning, big data platforms, and banking risk management.
Summary Generated by Built In
About this role:
Wells Fargo is seeking a Senior Quantitative Analytics Specialist.
In this role, you will:
10 Sep 2026
*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
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. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
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.
Wells Fargo is seeking a Senior Quantitative Analytics Specialist.
In this role, you will:
- Perform highly complex activities related to creation, implementation, and documentation
- Use highly complex statistical theory to quantify, analyze and manage markets
- Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives
- Utilize structured securities and provide expertise on theory and mathematics behind the data
- Manage market, credit, and operational risks to forecast losses and compute capital requirements
- Participate in the discussion related to analytical strategies, modeling and forecasting methods
- Identify structure to influence global assessments, inclusive of technical, audit and market perspectives
- Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills
- 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
- Required to work individually or as part of a team on multiple data science projects and work closely with business partners across the organization. Mentor and coach budding Data Scientist on developing and implementing data science solutions.
- Perform various complex activities related to statistical/machine learning. Provide analytical support for developing, evaluating, implementing, monitoring and executing models across business verticals using emerging technologies including but not limited to Python, Spark, and H2O etc.
- Expert knowledge on working on large datasets using SQL and present conclusions to key stakeholders.
- Establish a consistent and collaborative framework with the business and act as a primary point of contact in delivering the solutions.
- Experience in building quick prototypes to check feasibility and value to business.
- Expert in developing and maintaining modular code-base for reusability
- Review and validate models and help improve the performance of the model under the preview of the banking regulations.
- Work closely with technology teams to deploy the models to production.
- Prepare detailed documentations for projects for both internal and external that complies regulatory and internal audit requirements
- Working expertise in Tensorflow, Keras or Pytorch would be added advantage
- Working knowledge in developing end to end ML/AI pipeline in Apache Spark, Sparkling Waters, H2O, Caffe in Hortonworks/Cloudera and/or MapR or Teradata Aster big data platforms
- Ability to work with Data Engineers in discovering and optimizing bottlenecks in the AI/ML pipeline for real-time or near-real-time applications that consumes large throughput of data
- Master's degree in engineering in computer science, Information technology, Electrical Engineering etc.
- M.Sc./M.Phil. in statistics/ economics/ mathematics/ operations research engineering physics.
- 4 + years of relevant hands on experience in data science and advanced analytics.
- Must have hands on exposure in Python, PySpark and SQL.
- Expert knowledge of libraries like sckit-learn, pandas, numpy, mllib, matplotlib, keras.
- Expert in data mining and statistical analysis.
- Experience in developing, implementing models.
- Statistical models - linear regression, logistic regression, time series analysis, multivariate statistical analysis.
- Machine learning models - Random forest, XGBoost, GBM, SVM.
- Exposure to deep learning framework - ANN,RNN, CNN, LSTM
- Excellent understanding of model metrics including AUC, ROC, F-statistics etc. with clear understanding of how model performance is tuned
- Strong programing skills.
- Hands on knowledge in one or more of Big Data skills - SQL, Aster, Teradata, Hadoop, SPARK, H20, BigQuery.
- Exposure to Google Cloud Platform
- Critical thinking and strong problem solving skills
- Ability to learn the business aspects quickly
- Knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.is desirable
- Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry is desirable
- Ability to multi-task and prioritize between projects
- Ability to work independently and as part of a team
- Senior Quantitative Analytics Specialist is a partner-facing role and is responsible for delivering high impact analytic and data science projects by using analytics and AI.
Primary role of the advanced analytics consultant in the Consumer Modeling COE is to apply business knowledge and advanced programming skills and analytics to serve as a subject matter expert, analyst, advisor and consultant to support model lifecycle - model development, performance testing, data analysis, model implementation, model production, delivery of model results, change management, documentation and governance.
10 Sep 2026
*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
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. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
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.
Skills Required
- 4+ years of Quantitative Analytics experience or equivalent demonstrated through work experience, training, military experience, or education
- Master's degree or higher in mathematics, statistics, engineering, physics, economics, computer science, or another quantitative discipline
- Hands-on experience with Python, PySpark, and SQL
- Strong programming skills
- Experience in data mining and statistical analysis
- Experience developing and implementing statistical or machine learning models
- Knowledge of statistical models including linear regression, logistic regression, time series analysis, and multivariate statistical analysis
- Knowledge of machine learning models including random forest, XGBoost, GBM, and SVM
- Knowledge of model performance metrics including AUC, ROC, and F-statistics
- Knowledge of one or more big data technologies including SQL, Aster, Teradata, Hadoop, Spark, H2O, or BigQuery
- Ability to work independently and as part of a team
- Critical thinking and strong problem-solving skills
- Experience with TensorFlow, Keras, or PyTorch
- Experience developing end-to-end machine learning or AI pipelines
- Experience with deep learning frameworks or architectures including ANN, RNN, CNN, or LSTM
- Experience deploying models to production and collaborating with data engineering teams
- Knowledge of banking products, risk, marketing, operations, or supply chain functions
- Exposure to Google Cloud Platform
- Experience working with large datasets and presenting conclusions to stakeholders
- Experience mentoring or coaching data scientists
Wells Fargo Compensation & Benefits Highlights
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Healthcare Strength — Health coverage begins on day one with comprehensive medical, dental, and vision options, and the company subsidizes a substantial share of premiums for U.S. employees (varying by compensation band).
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Retirement Support — A robust 401(k) program includes an employer match for eligible employees, with specifics laid out in plan materials and filings.
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Parental & Family Support — Paid parental leave extends up to 16 weeks for eligible primary caregivers, alongside fertility coverage, adoption/surrogacy reimbursement, and lactation support.
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The Company
What We Do
Wells Fargo & Company (NYSE: WFC) is a leading financial services company that has approximately $2.2 trillion in assets. 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. 33 on Fortune’s 2025 rankings of America’s largest corporations. Our technology professionals drive innovation, information security, and big data analytics while maintaining a network that handles more than 12 billion customer interactions a year. Join us! Are you looking for more? Find it here. At Wells Fargo, we're more than a financial services leader – we’re a global trailblazer committed to driving innovation, empowering communities, and helping our customers succeed. We believe that a meaningful career is much more than just a job – it’s about finding all of the elements to help you thrive, in one place. Living the Well Life means you’re supported in life, not just work. It means having robust benefits, competitive compensation, and programs designed to help you find work-life balance and well-being. You’ll be rewarded for investing in your community, celebrated for being your authentic self, and empowered to grow. And we’re recognized for it — Wells Fargo continues to rank on the LinkedIn Top Companies lists of best workplaces “to grow your career.” All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic. © 2026 Wells Fargo Bank, N.A. All rights reserved. Member FDIC.
Why Work With Us
We're known for our “Well Life” approach to supporting employees’ career aspirations, work-life balance, and mental and physical health. Wells Fargo continues to rank on the LinkedIn Top Companies lists of best workplaces “to grow your career.”
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Wells Fargo Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Typical time on-site:
3 days a week
