Lead Analytics Consultant

Wells Fargo is seeking a Lead Analytics Consultant to lead the development and modernization of front-line risk monitoring analytics across BOS. This role will drive the design, development, and implementation of end-to-end monitoring solutions leveraging Python, SQL, SAS, AI, and cloud-based technologies to identify emerging risks, automate workflows, and generate actionable insights. The position will play a critical role in BOS's analytics transformation by leading SAS-to-Python migration efforts, advancing AI-powered monitoring capabilities, establishing analytical standards and best practices, and mentoring junior team members. The successful candidate will contribute to delivering Risk Clarity and Operational Excellence through innovative, scalable, and data-driven monitoring solutions.

• Advise line of business and companywide functions on business strategies based on research of performance metrics, trends in population distributions, and other complex data analysis to maximize profits and asset growth and minimize operating losses within risk and other operating standards.
• Provide influence and leadership in the identification of new tools and methods to analyze data.
• Ensure adherence to compliance and legal regulations and policies on all projects managed.
• Provide updates on project logs, monthly budget forecasts, monthly newsletters, and operations reviews.
• Assist managers in building quarterly and annual plans and forecast future market research needs for business partners supported.
• Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to resolve issues and achieve goals.
• Lead projects, teams, or serve as a peer mentor to staff, interns, and external contractors.

• 5+ years of Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, or education.
• Advanced hands-on expertise in Python for analytics, anomaly detection, and scalable monitoring solutions.
• Practical exposure to agentic AI and LLM usage for analytics acceleration or automation.
• Experience working with GCP or other cloud-based analytics platforms.
• Strong SQL skills with experience handling large, complex datasets.
• Solid working knowledge of SAS in risk monitoring or regulatory environments.
• Strong experience designing and reviewing visualizations in Power BI, Tableau, and Python.

• Proven ability to lead end-to-end analytical solution design and guide junior team members.
• Strong understanding of data modeling, feature engineering, and analytics architecture.
• Prior experience driving analytics standardization or modernization initiatives.

• Applicants must be willing to work onsite.
• Applicants must be willing to work mid-shift and night-shift schedules.
• Lead the design, delivery, and evolution of front-line monitoring analytics to detect conduct, operational, and compliance risks across BOS. The role will own end-to-end risk monitoring solutions that identify trends, anomalies, and outliers, driving improvements in monitoring coverage, consistency, scalability, and timeliness.
• Lead complex analytical solutioning using Python, SQL, and SAS, including data preparation, metric and feature design, anomaly detection frameworks, and visualization development.
• Provide technical leadership across multiple monitoring initiatives, ensure analytical rigor, and guide effective risk identification, escalation, and insight generation.
• Play a key leadership role in BOS analytics modernization, including SAS-to-Python migration, adoption of GCP-based analytics environments, and automation of monitoring workflows. The role will establish analytics standards, drive documentation and reusability, review peer work, and mentor junior consultants. Exposure to agentic AI, LLM-enabled analytics, and advanced modeling approaches is strongly preferred.
• Support BOS Front-Line Monitoring's mandate to drive Risk Clarity and Operational Excellence through AI-powered analytics modernization.
• Contribute to the transformation of monitoring capabilities from rule-based and fragmented alerting to AI-driven, behavioral, and trend-based monitoring solutions leveraging Python, GCP, and agentic AI technologies.
• Provide senior technical ownership in designing and scaling end-to-end monitoring solutions, leading SAS-to-Python migration efforts, automating workflows, and ensuring analytics remain explainable, defensible, and audit-ready.
• Enable organizational capability building by establishing standards, mentoring junior consultants, and operationalizing AI and agentic capabilities that are foundational to the future-state operating model of Front-Line Monitoring