Senior Data Science consultant

About this role:

Wells Fargo is seeking a Senior Data Science Consultant to support the Data Insights and Analytics (BIA) team within the Wells Fargo Home Lending (WFHL) group under Consumer Lending (CL) LOB. The role involves dissecting and comprehending complex high risk lending processes and corresponding dataflows. The primary objective is to pinpoint and analyze gaps within these processes, ensuring alignment with policies and regulations. This requires adept data analysis skills and a keen understanding of the intricacies of home lending to enhance compliance and mitigate risks effectively.

In this role, you will:

• Lead or participate in moderately complex initiatives and deliverables by utilizing data-driven, advanced analytical, statistical techniques, algorithms, or models to make actionable insights, trends, recommendations, or contribute to large-scale planning that has a broader impact
• Review and analyze moderately complex, large structured and unstructured data sets from various sources, requiring an in-depth hypothesis generation and advanced analysis of variable factors to convert data into meaningful insights and recommendations
• Independently analyze and resolve moderately complex issues and lead team to meet deliverables while leveraging solid understanding of analytic capabilities
• Collaborate and consult with peers, colleagues, and mid-level 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 mentor for lower-level staff
• Execute 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
• Communicate actionable insights and recommendations using data in a digestible format to a non-technical audience of varying levels

Required Qualifications:

• 4+ years of experience in data science, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 6+ years of overall experience
• Data Analysis: Proficiency in extracting insights from large datasets, employing statistical methods, and utilizing tools like SAS, Python or SQL for thorough analysis
• Risk Assessment: Ability to assess and quantify risks in business processes, employing statistical models and risk management techniques
• Process Mapping: Expertise in mapping out complex processes while leveraging data, identifying key stages, and assessing potential areas of vulnerability or non-compliance
• Problem Solving: Adept at identifying problems, proposing innovative solutions, and implementing process enhancements to address gaps in the lending procedures
• Strong written and verbal communication, presentation and inter-personal skills
• Basic understanding of the US Home Lending process

Desired Qualifications:

• Domain and Regulatory Knowledge: Understanding of home lending process and corresponding regulations and compliance standards
• Data Visualization: Proficiency in creating compelling visualizations to communicate findings effectively, using tools like Tableau, Power BI, or other similar platforms
• Audit Experience: Possess hands-on audit experience, demonstrating the ability to conduct thorough assessments of the processes, which includes a keen eye for detail.

Job Expectations:

• Data Exploration and Analysis: Dive into extensive datasets related to high-risk home lending processes, employing data analysis tools to extract meaningful insights, identify patterns, trends and anomalies that could impact compliance
• Risk Assessment and Mitigation: Utilize risk management techniques to assess and quantify risks, while proposing and implementing strategies to mitigate these effectively
• Process Mapping: Map out the end-to-end lending sub process in combination with the data process flow, identify key stages and potential bottlenecks, with good benchmarking strategies
• Collaboration with Stakeholders: Work closely with cross-functional teams, including compliance and business units, to understand the details of the process, communicate findings, implement changes, and ensure a cohesive approach to risk management
• Communication and Reporting: Clearly communicate complex findings and insights to both technical and non-technical stakeholders through viz reports and other appropriate channels

Ultimately the role is pivotal in ensuring that the organizations high-risk home lending processes are not only data-driven but also compliant with policies and regulations, thereby minimizing risks and fostering a secure lending environment.