Senior Lead Analytics Consultant

Wells Fargo•Minneapolis, MN

1d•$139,000 - $239,000•Hybrid

About The Position

Wells Fargo is seeking an independent, self-starting analytics professional for a hands-on individual contributor role focused on data engineering, modeling, advanced analytics, and production deployment. The role supports identification and mitigation of current and emerging risks, including employee misconduct, employee-enabled fraud, regulatory risks, and reputational risks. The successful candidate will help transform the analytics team as it expands the use of AI-assisted development and modern analytics capabilities. Within Consumer Banking and Lending (CBL), this position acquires, models, and prepares data to operationalize data-driven detection strategies, and takes analytics and machine learning solutions from prototype through production. The role partners across risk functions to provide operational support that helps deliver products and services to customers. It requires advanced Python skills, SAS coding experience, fluency with AI-assisted development, strong data engineering and analytical capabilities, and the ability to translate complex real-world problems into practical, scalable solutions. The position has a hybrid work schedule and is not eligible for visa sponsorship. It is based at one of the required Wells Fargo locations listed in Charlotte, North Carolina; Chandler, Arizona; Minneapolis, Minnesota; Irving, Texas; West Des Moines, Iowa; or San Antonio, Texas. The base pay range is $139,000 to $239,000, varying by location and other factors; employees may also be eligible for incentive opportunities or a discretionary bonus.

Requirements

At least 7 years of experience in analytics, reporting, financial modeling, or statistics, or equivalent demonstrated through work experience, training, military experience, education, or a combination.
Ability to independently lead highly complex technical work and coordinate activities across the enterprise.
Strong written and verbal communication skills, including the ability to explain complex analytical findings to senior business and risk stakeholders.
Ability to work effectively in fast-paced, exploratory environments while balancing innovation, production rigor, and regulatory and policy requirements.

Nice To Haves

Advanced proficiency in Python for data engineering, analytics, machine learning, automation, testing, and production-grade development.
Strong SAS coding skills, including developing, validating, and maintaining production data-preparation, analysis, and reporting workflows.
Experience designing and implementing advanced analytics, machine learning, natural language processing, or generative AI solutions using large-scale structured and unstructured data.
Experience with data acquisition, integration, modeling, and preparation for complex analytics and machine learning workflows.
Experience identifying risk, anomalies, or behavioral patterns through analytics, preferably in monitoring, financial services, compliance, or risk management.
Ability to design fit-for-purpose model evaluation approaches, including custom evaluation methods when standard metrics are insufficient.
Experience building reusable frameworks, standards, and automated production pipelines for scalable, repeatable analytics solutions.
Familiarity with data quality, schema design, metadata management, data governance, documentation, and controls for sensitive data.
Fluency with generative AI and AI-assisted development tools, such as GitHub Copilot, throughout the development lifecycle.
Ability to evaluate emerging technologies and influence analytics practices beyond a single project or team.

Responsibilities

Serve as a subject matter expert in advanced analytics, machine learning, natural language processing, and other AI techniques to identify employee misconduct, employee-enabled fraud, and related conduct risks.
Independently design, develop, test, and operationalize end-to-end analytics and AI/ML solutions using structured and unstructured data, including emails and coaching notes.
Lead complex data acquisition, engineering, modeling, and preparation activities to move analytics and AI/ML risk-detection solutions from prototype to production.
Establish reusable methodologies, frameworks, coding standards, and development patterns in Python and SAS for scalable analytics adoption across Front Line Monitoring (FLM) and broader business operations.
Evaluate emerging AI and analytics technologies and select practical, scalable approaches for complex monitoring and risk-detection needs.
Use AI-assisted development tools to accelerate coding, testing, documentation, and solution refinement while maintaining appropriate human review and controls.
Analyze sensitive, large-scale data to identify emerging patterns, anomalies, and risk signals, and translate findings into actionable insights for business and risk management stakeholders.
Provide technical leadership and expert guidance to senior leaders, analytics teams, and cross-functional partners while coordinating complex enterprise activities.
Ensure solutions comply with legal, regulatory, data governance, model risk, information security, and enterprise policy requirements.
Follow applicable Wells Fargo risk programs, policies, procedures, and compliance obligations; monitor and escalate issues and make sound risk decisions.

Benefits

Competitive salary and potential incentive opportunities or discretionary bonus.
Health benefits.
401(k) Plan.
Paid time off.
Disability benefits.
Life insurance, critical illness insurance, and accident insurance.
Parental leave.
Critical caregiving leave.
Discounts and savings.
Commuter benefits.
Tuition reimbursement.
Scholarships for dependent children.
Adoption reimbursement.
Programs supporting work-life balance and well-being.