WLS - Data & Reporting Business Manager - Vice President

Job Responsibilities

• Serve as a senior analytics advisor to business and finance leadership, shaping the insights agenda and ensuring high-quality deliverables
• Own partnerships between data management and business stakeholders, aligning priorities and accelerating resolution of data issues
• Lead proactive data health programs, including control checks, root-cause analysis, and remediation planning
• Define, standardize, and govern portfolio metrics to ensure consistency, control, and audit readiness
• Translate performance, risk, and operational data into clear, decision-ready insights with recommended actions
• Lead analytical work end-to-end, from problem definition through execution and implementation
• Develop executive-level materials that clearly communicate analytical findings, data quality, and risk implications
• Drive automation and self-service capabilities to improve efficiency, control, and adoption
• Apply advanced analytics to business use cases, partnering with technical teams to develop scalable solutions
• Establish responsible use of artificial intelligence tools, including validation, explainability, and governance practices
• Evaluate analytical outputs to ensure accuracy, clarity, and readiness for senior stakeholders

Required Qualifications, Capabilities, And Skills

• 7 years of experience in data science, analytics, or data-driven strategy in a complex or regulated environment
• Proven ability to drive analytics and data integrity outcomes across cross-functional teams
• Strong data analysis skills, including metric design, statistical analysis, and data quality assessment
• Experience defining and governing business-critical metrics with appropriate controls and documentation
• Hands-on experience leading data quality initiatives and remediation efforts
• Strong business acumen with the ability to connect analytics to performance, risk, and operational decisions
• Executive communication skills with the ability to deliver clear, concise insights and recommendations
• Strong analytical judgment with a focus on accuracy and quality of outputs
• Experience applying artificial intelligence tools with appropriate validation and oversight
• Proficiency in data visualization and presentation tools

Preferred Qualifications, Capabilities, And Skills

• Experience with programming languages such as Python or SQL to develop analytics solutions
• Familiarity with responsible artificial intelligence principles in a controlled environment
• Knowledge of data governance frameworks, including metric governance and data lineage
• Experience in financial services, lending, or portfolio and risk-related environments
• Experience working in finance or business management functions
• Experience acting as a liaison between technical data teams and business stakeholders