Department Overview
Model Risk Management (MRM): Wells Fargo’s Model Risk Management is responsible for independently overseeing the management of model risk exposures across the enterprise (including governing, monitoring, and reporting on aggregate model risk exposures, model validations, and model oversight across enterprise). This oversight extends to all phases of a model’s life cycle, including identification, development, validation, implementation, finding resolution, usage, performance monitoring, documentation, and retirement.
About this role
Wells Fargo is seeking a Senior Quantitative Analytics Specialist.
MRM operates in a fast-paced work environment with continuously changing policies and technologies. The successful candidate is expected to be self- motivated, require minimal supervision, and produce work that is consistent with MRM’s recognized high standards. Effective work will involve familiarity with source systems of record, analytical data and sampling plans, model replications, model performance assessments, and test model development as effective challenges to lines of business. It further requires strength in writing detailed standard analytical reports to ensure Wells Fargo’s compliance with governance policies and regulations. Each validation report will include assessments of the specific business, model purpose and history, the model methodology, data integrity, model development, performance, implementation, and monitoring. These documents are read by a broad audience, including auditors and regulators.
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
Required Qualifications
- 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
Desired Qualifications
- 4+ years of experience with minimum Masters/Phd in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis
- Performing model validations and clearly documenting evidence of validation activities
- Develop benchmarking and alternative models in Python/SAS
- Providing effective challenge to models developed in/for the lines of business, including identifying conceptual weaknesses in a model and understanding tradeoffs with other approaches
- Managing and mitigating model risk to meet or exceed regulatory and industry standards
- Providing leadership and consultation to less experienced validators and business partners
- Communicating model risk findings and limitations to key stakeholders
- Contributing to the improvement of model building and model use practices
- Providing analytical support and offering insights regarding a wide array of business initiatives
- Interacting with senior management and regulators on key modeling issues, including the identification, management, and mitigation of model risk
- Proactively following the industry trend to apply and develop new technology to improve efficiency
- Strong mathematical, statistical, analytical and computational skills
- Able to demonstrate first-hand knowledge of advanced topics in various mathematical and numerical methods such as Monte Carlo, stochastic calculus, differential equations, linear algebra, applied probability, statistics and machine learning knowledge
- Eagerness and ability to learn new technologies and programming languages
- Strong communication skills for a variety of audiences (other technical staff, senior management and regulators) both verbally and in writing
- Capability to multi-task and finish work within strict timelines and provide timely requests for information and follow-up questions
- Ability to work independently on complex model validations from start to finish
- Skill in managing relationships with key model stakeholders
- Eagerness to contribute collaboratively on projects and discussions
- Perpetual interest in learning something new but being comfortable with not knowing all the answers.
- Attention to detail in both analytics and documentation
- Aptitude for synthesizing data to 'form a story' and align information to contrast/compare to industry perspective
- Intellectually curious, who enjoy solving problems
Job Expectations
- MRM serves as the second line of defense to ensure the integrity of Wells Fargo’s model inventory. A Senior Quantitative Analytics Specialist is an individual contributor role. This position will focus primarily on Mortgage, Credit and Market Risk model validations. However, frequent special projects and seasonal requirements for CCAR validations will provide a variety of modeling contexts throughout each year. A validation project typically begins and ends with the analyst, requiring broad and continuous attention to detail, comprehensive documentation, and interactions with developers. Meetings with auditors and regulators will require recall of validation details.
- A Senior Quantitative Analytics Specialist should have a deep academic knowledge, broad based approach to solutioning business problems. He/she should approach the problem agnostic of analytic technique, tool or process. Ability to think outside the box and provide ensemble solutions should set them apart to be a high performing team member
Posting End Date:
20 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
.
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b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.