Lead Data Science Consultant

In this role, you will:

• Lead complex initiatives by utilizing data-driven, advanced analytical, statistical techniques, algorithms, or models to make actionable insights, trends, recommendations, including those that are cross-functional with broad impact acting as key participant in large-scale planning

• Review and analyze complex, multi-faceted, larger-scale, or longer-term business, operational, or technical challenges that require in-depth hypothesis generation and advanced analysis of multiple parts, including intangibles or unprecedented factors

• Make decisions in complex and multi-faceted situations requiring an expertise in analytical thinking to resolve abstract business issues that influence and lead broader work team to meet deliverables and drive new initiatives

• Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to drive recommendations and strategies based on data driven, analytical insights, trends, and patterns that will resolve issues and achieve goals; may lead projects, teams or serve as a peer mentor

• Execute complex analytical experiments and create innovative statistical models to discover solutions for abstract business problems across various domains

• Interpret and analyze data, using advanced analytics modeling methods and programming, to recommend ways to solve problems and influence business decisions and strategies

• Provide consultation to peers on data science best practices, methods, and tools to leverage

• Communicate actionable insights and recommendations using data in a digestible format to a non-technical audience of varying levels

Required Qualifications:

• 5+ years of data science experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• Great experience in data analytics, reporting, or data science

• 5+ years of experience in Consumer Lending / Retail Banking analytics

• Strong proficiency in SQL and advanced analytics using Python or R

• Experience with BI and visualization tools such as Tableau, Power BI, or equivalent

• Proven ability to work with large, complex datasets

• Strong stakeholder management and communication skills

• Advanced degree in Data Science, Statistics, Economics, Engineering, or related field

• Experience with Consumer Lending lines of business and systems of record

• Knowledge of credit risk metrics and portfolio analytics (delinquency, roll rates, losses, vintage analysis)

• Exposure to model governance, performance monitoring, or challenger models

• Experience working in a Global Capability Center (GCC) or offshore model

• Familiarity with cloud analytics platforms (AWS, Azure, or GCP)

Job Expectations:

• Willingness to work on-site 3 days a week at a Wells Fargo Risk hub location

• Proven track record of building and maintaining strong working relationships and coordinating with stakeholders to achieve goals

• Strong analytical skills with high attention to detail and accuracy

• Ability to articulate complex concepts in clear manner

• Ability to exercise independent judgment and creative problem-solving techniques.

• Lead and mentor a team of data scientists, analysts, and BI developers

• Drive best practices in analytics delivery, agile execution, and documentation.

• Support hiring, performance management, and skill development within the team.

•  Lead design and delivery of advanced analytics and reporting for Consumer Lending portfolios

• Translate complex business needs into scalable analytics and reporting solutions

• Drive insights across the Home lending including Servicing, portfolio performance, losses, and profitability

• Partner with Consumer Lending , Credit Risk, Finance, and Product teams to influence data‑driven decisions

• Present analytics, trends, and recommendations to senior leadership

• Ensure compliance with model risk management, data governance, and regulatory reporting standards

• Mentor and guide junior analysts and data scientists

• Support reporting automation, efficiency initiatives, and analytics modernization

• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science