Senior Data Science Consultant

Wells Fargo Bank•Charlotte, NC

22h•Hybrid

About The Position

Wells Fargo is seeking a Senior Data Science Consultant responsible for leveraging advanced data analytics to solve complex business challenges and influence enterprise-wide strategies. In this role, you will develop and deliver advanced customer and banker placement analytics, including segmentation, portfolio optimization, performance analysis, and opportunity sizing. You will analyze large, complex datasets to identify trends, risks, and opportunities related to customer coverage, banker capacity, and client outcomes. You will also design repeatable analytical frameworks to support strategic initiatives, governance reviews, and leadership reporting, ensuring analytical outputs are accurate, auditable, and aligned with enterprise data and governance standards. You will execute highly complex analytical experiments and create innovative statistical models to discover solutions for abstract business problems across various domains. You will partner with sales leadership teams to inform placement strategy and customer alignment decisions, and support enterprise initiatives related to customer assignment, servicing models, and coverage optimization. Additionally, you will translate analytical findings into clear business recommendations, highlighting tradeoffs and implications, and build executive-ready presentations (PowerPoint and verbal) for senior leaders, including SVPs and executive committees. You will clearly communicate complex analytical concepts to non-technical audiences using data storytelling and visualizations, and respond to ad hoc leadership requests with concise, high-impact analyses and recommendations. You will collaborate with cross-functional partners (Analytics, Banking, Risk, Operations, Technology) and support governance processes by ensuring analytical outputs meet internal standards and documentation requirements, acting as a trusted analytics advisor to stakeholders across the organization.

Requirements

4+ 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

Master’s degree (MBA, MS, or equivalent) in Analytics, Data Science, Business, or related discipline.
Experience in banking, financial services, customer analytics, or coverage/placement models.
Proficiency in SQL, Python, R, or similar analytical tools.
Experience developing dashboards or standardized reporting for leadership.
Familiarity with governance, risk, or compliance considerations in analytics.

Responsibilities

Develop and deliver advanced customer and banker placement analytics, including segmentation, portfolio optimization, performance analysis, and opportunity sizing.
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.