Data Science Director

Wells Fargo•Irving, TX

1d•$185,000 - $300,000•Hybrid

About The Position

Wells Fargo is seeking a Data Science Director to lead a broad, strategic analytics portfolio within Digital, Data & AI. This role is accountable for defining analytics strategy, setting the operating model, and leading high-performing teams that deliver decision support, measurement frameworks, and scalable insight capabilities across digital, mobile, and cross-channel customer experiences. The leader in this role will partner closely with senior Product, Digital, Technology, Risk, and Business leaders to shape priorities, modernize analytics through automation, and drive measurable outcomes across Fargo, product analytics, identity and authentication, performance and behavioral insights, customer research, BEV, glass box diagnostics, and analytics governance. This position requires a strong balance of strategic vision, organizational leadership, operational rigor, and executive influence, with a focus on building durable analytics capabilities that improve customer experience, business performance, and enterprise decision-making. Learn more about the career areas and lines of business at wellsfargojobs.com.

Requirements

10+ years of data science experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
4+ years of management or leadership experience
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Nice To Haves

Experience in digital, mobile, product, or channel analytics, preferably within financial services or other highly regulated environments
Exceptional executive communication and influence skills, with the ability to shape strategy and drive alignment across senior leaders and complex stakeholder groups
Demonstrated success leading complex, cross-functional analytics transformations spanning measurement, governance, automation, and operating model design
Experience with experimentation, time-series analysis, customer research integration, and product performance measurement in digital environments
Experience modernizing analytics platforms, instrumentation, or governance practices to support scalable, self-service, and transparent decisioning

Responsibilities

Set the vision, strategy, and multi-year roadmap for digital, mobile, and cross-channel analytics, ensuring alignment to enterprise priorities, customer outcomes, product strategy, risk requirements, and business growth.
Identify opportunities for automation and leveraging AI
Serve as a trusted advisor to senior executives by translating complex data into clear strategic insights, performance narratives, and decision-ready recommendations that influence roadmap, investment, and experience design decisions.
Lead cross-functional partnerships across Product, Digital, Engineering, Risk, Fraud, Marketing, Operations, Customer Experience, and Research to embed analytics into strategic planning, prioritization, experimentation, and product delivery.
Own analytics for digital and mobile customer journeys (including identity and authentication, developing an integrated view of engagement, conversion, satisfaction, friction points, and value creation across channels and experiences.
Lead the strategy for cross-channel analytics automation, scaling governed data products, standardized dashboards, reusable measurement assets, and self-service insight capabilities to reduce manual reporting and accelerate decision-making.
Provide executive leadership for Fargo analytics, measuring discovery, engagement, containment, customer outcomes, and experience quality to inform prioritization, optimization, and responsible scaling of AI-powered experiences.
Oversee product-specific analytics across priority digital capabilities and experiences, including feature adoption, funnel performance, customer behavior, experimentation, and business impact measurement.
Direct analytics for identity and authentication experiences, balancing customer ease, fraud mitigation, security controls, and conversion outcomes through rigorous measurement, diagnostics, and insight generation.
Lead performance and insights analytics using trend analysis, time-series methods, and behavioral diagnostics to identify performance drivers, emerging issues, and opportunities for optimization across digital and mobile channels.
Establish enterprise-grade measurement frameworks for digital, mobile, and product experiences, including KPI definitions, attribution and causal measurement approaches, test-and-learn design, and value realization tracking.
Advance transparency and accountability through BEV, glass box, and diagnostic analytics, enabling leaders to understand drivers of performance, operational tradeoffs, model behavior, and opportunities for continuous improvement.
Integrate customer research, voice-of-customer insights, and behavioral analytics to create a richer understanding of customer needs, pain points, journey friction, and emerging opportunity areas.
Establish and scale analytics governance across data definitions, metric standardization, instrumentation quality, controls, and risk management to improve consistency, trust, and reusability across teams.
Lead a modern analytics operating model that connects research, measurement, diagnostics, and automation to product and business decision-making, improving speed to insight and execution effectiveness.
Own a high-visibility analytics portfolio, balancing near-term delivery with long-term capability building while ensuring alignment to strategic priorities, funding decisions, and enterprise transformation goals.
Lead and develop multiple teams of managers, analysts, and data science professionals delivering complex, cross-functional analytics, measurement, and automation initiatives.
Establish and maintain strong standards for data accuracy, integrity, governance, model transparency, control effectiveness, and risk management across the analytics portfolio.
Provide thought leadership on advanced analytics methods, experimentation, time-series analysis, measurement science, and analytics modernization best practices.