Senior Quantitative Analytics Specialist

About this role:
Wells Fargo is seeking an experienced senior data scientist in ML and LLMs to drive our Predictive AI and Generative AI model initiatives. The ideal candidate will combine deep technical expertise with leadership skills to guide a team in developing cutting-edge business centric solutions.
In this role, you will:

• Design, build, and deploy machine learning and predictive AI models to solve complex business problems in banking and financial domains (e.g., Digital customer experience, fraud detection, forecasting)
• Collaborate closely with quantitative analysts and business stakeholders to understand requirements, develop solutions, and present insights
• Lead or contribute to GenAI-based proof-of-concepts and experimentation, exploring how generative techniques can enhance decision-making or automation in banking use cases
• Write efficient, production-grade code using Python and PySpark, and ensure scalability and robustness in a distributed computing environment
• Own the end-to-end model lifecycle including data exploration, feature engineering, model development, validation, deployment, and monitoring
• Apply rigorous testing and validation strategies to ensure models are explainable, auditable, and compliant with internal risk/governance standards
• Collaborate with data engineers, model validators, and product managers to ensure timely delivery and alignment with enterprise data architecture
• Show strong project ownership, proactively driving tasks, managing timelines, and communicating blockers or dependencies effectively

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
• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Essential Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or related field
• Minimum 4 years of experience in machine learning, predictive modeling, or quantitative analytics, preferably within financial services
• Strong programming skills in Python with hands-on experience using PySpark for large-scale data processing
• Solid understanding of statistical and machine learning concepts (e.g. supervised and unsupervised learning, time-series analysis, graph) and deep understanding of model evaluation
• Demonstrated ability to work independently, take ownership of projects, and manage multiple stakeholders across technical and business teams
• Excellent communication and storytelling skills, especially in translating technical outcomes to business insights

Desired Qualifications:

• Experience working in a regulated environment (e.g., banking, insurance, fintech) with exposure to model risk governance or regulatory modeling practices
• Exposure to Generative AI concepts (e.g., LLMs, transformers, prompt engineering) and experience in building or experimenting with generative and agentic solutions.
• Familiarity with AI frameworks (e.g. Langchain, Langgraph, PyTorch) for business applications
• Familiarity with MLOps and LLMOps tools and best practices of model orchestration
• Knowledge of quantitative finance, portfolio modeling, or risk management is a plus
• Experience in cloud environments (e.g., AWS, Azure, GCP) and containerized deployments (e.g., Docker, Kubernetes) is a bonus

Posting End Date:
29 Jul 2025
*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.