Lead Quantitative Analytics Specialist

About this role:

Wells Fargo is seeking a Lead Quantitative Analytics Specialist.

This is a partner-facing role and is responsible for delivering high impact analytic and data science projects across enterprise functions.

AIM is the centralized model development organization for the COO and enterprise functions, delivering Predictive AI, NLP, and Generative AI solutions aligned to strategic business priorities. The group operates as a designated Model Development Center, applying robust governance, reusable components, and mature delivery practices to responsibly commercialize AI at scale.

In this role, you will:

• Lead end‑to‑end development of predictive and statistical models, including problem formulation, feature engineering, model training, evaluation, deployment, and post‑production monitoring.
• Apply supervised, unsupervised, semi‑supervised, and time‑series modeling techniques to solve complex business problems across COO-CAO and enterprise portfolios.
• Design and implement models using Python‑based ML ecosystems (e.g., scikit‑learn, XGBoost, LightGBM, PySpark ML) with strong emphasis on scalability and reproducibility.
• Develop and maintain production‑ready codebases following enterprise standards for version control, testing, and documentation.
• Own model documentation artifacts aligned with enterprise Model Risk Management (MRM) standards, including methodology, assumptions, limitations, performance metrics, and monitoring plans.
• Partner with Model Risk, Audit, and Compliance teams to support independent validation, issue remediation, and regulatory exams.
• Perform rigorous model performance analysis, stability testing, bias assessment, and error diagnostics using appropriate statistical and ML metrics (e.g., AUC‑ROC, KS, precision‑recall, stability indices).
• Translate business problems into analytical problem statements and communicate complex modeling outcomes clearly to non‑technical stakeholders.
• Act as a trusted analytics advisor to product, operations, risk, and control partners, enabling data‑driven decision making.
• Present analytical findings, model insights, and recommendations to senior leadership with clarity and impact.
• Lead multiple analytics initiatives concurrently, ensuring on‑time, high‑quality delivery across the model lifecycle.
• Collaborate closely with data engineers, platform teams, BI/UI specialists, and MLOps partners to deploy and scale models.
• Contribute to reusable model components, accelerators, and best practices that improve AIM delivery velocity and quality.
• Mentor junior data scientists and analysts; contribute to building a strong Predictive AI talent pipeline.

Required Qualifications:

• 8+ 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 field such as mathematics, statistics, engineering, physics, economics, or computer science.

• Demonstrated experience delivering multiple end‑to‑end modeling projects in production environments.
• Strong expertise in Python programming and core data science libraries for modeling, analysis, visualization, and automation.
• Deep understanding of machine learning algorithms, statistical modeling, and time‑series analysis.
• Proven ability to manage complex analytical problems and drive alignment across geographically distributed teams.
• Excellent analytical rigor, organizational skills, and attention to detail across data analysis, code management, and documentation.
• Demonstrated excellence at identifying stakeholders, understanding needs, and driving to resolution.

Desired Qualifications:

• Excellent verbal, written, and interpersonal communication skills.
• Experience in Banking, Financial Services, or regulated enterprise environments.
• Proficiency with SQL, large‑scale data platforms (e.g., BigQuery, Hive, Spark), and distributed computing.
• Experience developing models using PySpark, and managing code with Git/GitHub.
• Familiarity with automated ML and workflow orchestration tools (e.g., H2O, DataRobot, Airflow).
• Hands‑on experience with cloud platforms (GCP, Azure, AWS) for model development and deployment.
• Knowledge of deep learning techniques (ANN, CNN, RNN, DNN) and practical considerations for architecture design.
• Exposure to unstructured data problems, including NLP, text mining, or voice/digital analytics.
• Strong understanding of model monitoring, drift detection, and lifecycle management.
• Advanced proficiency in PowerPoint and Excel for executive‑level communication.

Job Expectations:

• Lead and deliver Predictive AI initiatives in partnership with a Data Science Manager while also operating independently on complex modeling efforts.
• Collaborate with cross‑functional teams to deliver production‑grade, MRM‑compliant analytical solutions.
• Contribute to talent development, mentoring, and fostering a culture of technical excellence and innovation within AIM.
• Help shape best practices, standards, and strategic direction for Predictive AI modeling within the COO. Adapt at attracting, hiring and retaining top notch data science talents and build world class team

Posting End Date: 

3 Apr 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.