Senior Lead Data Science Consultant

Wells Fargo & Company•Minneapolis, MN

3d•$159,000 - $279,000•Hybrid

About The Position

Wells Fargo is seeking a Senior Lead Data Science Consultant within their analytics team for Business Banking. This role will be responsible for developing and delivering advanced customer and banker placement analytics, including segmentation, portfolio optimization, performance analysis, and opportunity sizing. The role involves analyzing large, complex datasets to identify trends, risks, and opportunities related to customer coverage, banker capacity, and client outcomes. It also requires designing repeatable analytical frameworks for strategic initiatives, governance reviews, and leadership reporting, ensuring accuracy and alignment with enterprise data standards. The consultant will execute complex analytical experiments and create innovative statistical models to solve business problems, partnering with sales leadership to inform placement strategy and customer alignment. Support will be provided to enterprise initiatives concerning customer assignment, servicing models, and coverage optimization. The role demands translating analytical findings into clear business recommendations, highlighting tradeoffs, and building executive-ready presentations for senior leaders. Communication of complex analytical concepts to non-technical audiences through data storytelling and visualizations is key. The position also involves responding to ad-hoc leadership requests, collaborating with cross-functional partners, and acting as a trusted analytics advisor.

Requirements

7+ years of data science 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

Nice To Haves

Experience in banking, financial services, customer analytics, or coverage/placement models
Expertise in advanced analytics and data tools (e.g., SQL, Python, R, SAS) with hands-on experience in deep-dive analysis and data mining
Proficiency in data visualization and BI platforms (e.g., Power BI, Tableau, Alteryx) to develop interactive dashboards and reporting frameworks
Experience developing KPI frameworks, building business cases, and quantifying the financial impact of strategic initiatives
Familiarity with governance, risk, or compliance considerations in analytics.
Strong experience engaging executive stakeholders, including delivering clear, data-driven insights and recommendations to senior leadership
Strong analytical skillset, including experience with data analysis, modeling, and interpretation.
Experience working with structured datasets from enterprise data sources.
Strong business acumen with the ability to align analytics initiatives to enterprise goals, risk considerations, and regulatory/compliance needs
Ability to operate independently, navigate ambiguity and manage multiple priorities in a fast‑paced environment.

Responsibilities

Analyze large, complex datasets to identify trends, risks, and opportunities related to customer coverage, banker capacity, and client outcomes.
Design repeatable analytical frameworks to support strategic initiatives, governance reviews, and leadership reporting.
Ensure analytical outputs are accurate, auditable, and aligned with enterprise data and governance standards.
Execute highly complex analytical experiments and create innovative statistical models to discover solutions for abstract business problems across various domains.
Partner with sales leadership teams to inform placement strategy and customer alignment decisions.
Support enterprise initiatives related to customer assignment, servicing models, and coverage optimization.
Translate analytical findings into clear business recommendations, highlighting tradeoffs and implications.
Build executive‑ready presentations (PowerPoint and verbal) for senior leaders, including SVPs and executive committees.
Clearly communicate complex analytical concepts to non‑technical audiences using data storytelling and visualizations.
Respond to ad‑hoc leadership requests with concise, high‑impact analyses and recommendations.
Collaborate with cross‑functional partners (Analytics, Banking, Risk, Operations, Technology).
Support governance processes by ensuring analytical outputs meet internal standards and documentation requirements.
Act as a trusted analytics advisor to stakeholders across the organization.