About this role:
Wells Fargo is seeking a Lead Quantitative Analytics Specialist.
In this role, you will:
- Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly statistical theory
- Qualify monitor markets and forecast credit and operational risks
- Strategize short and long-term objectives, and provide analytical support for a wide array of business initiatives
- Utilize stochastic, structured securities, spread analysis, with the expertise in the theory and mathematics behind the analysis
- Review and assess models inclusive of technical, audit, and market perspectives
- Identify structure and scope of review
- Enable decision making for product and marketing with broad impact and act as key participant to develop and document analytical models
- Collaborate and consult with regulators and auditors
- Present results of analysis and strategies
Required Qualifications:
- 5+ 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
Desired Qualifications:
- Required to work individually or as part of a team on multiple data science and artificial intelligence projects and work closely with business partners across the organization. Mentor and coach budding Data Scientists 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, Agentic AI frameworks like ADK, GCP vertex AI and NLP.
- Expert knowledge on working on large datasets using vector databases like Redis, Elastic Search, FAISS.
- 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 multiple teams such as technology, AI/ML Ops, MRM teams to deploy the models to production.
- Prepare detailed documentations for projects for both internal and external that complies regulatory and internal audit requirements
- Mentor and guide junior team members and work on multiple analytics/data science initiatives.
Job Expectations:
- Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
- 5+ years Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Demonstrated expertise in Generative AI, including large language models, Generative AI frameworks, and advanced NLP techniques which includes leading GenAI projects from conception to production
- 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
- 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, experience in working on LLMs. Exposer to Agentic AI frameworks.
- 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
Posting End Date:
21 May 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.
