Vice President, Data and Analytics

Position Summary

The Vice President, Data and Analytics is a strategic, enterprise-level leader responsible for transforming data into insights that drive decision-making, performance, and profitable growth. This role oversees the design, delivery, and governance of data science and analytics across the organization-spanning marketing, financial, operational, customer, and people data - and leads the software and data engineering required to power those analytics.

The ideal candidate is an exceptional business partner and thought leader who can translate complex data into clear narratives, influence executive decisions, and build a high-performing engineering team.

Key Responsibilities

Strategy & Leadership

• Define and lead the enterprise data and analytics strategy, aligned to the company's strategic priorities and financial goals.

• Serve as the data and analytics advisor to the Executive Leadership Team, providing insight into revenue, profitability, cost optimization, customer trends, and operational performance.

• Identify and prioritize analytics initiatives and resources based on business impact, ROI, and strategic value.

• Champion a data-driven culture, embedding analytics in planning, forecasting, and performance management.

• Partner closely with the CIO/CTO to develop a multi-year technology strategy with data at the foundation.

Analytics & Insights

• Oversee the development of standard dashboards, scorecards, and self-service reporting for executives and functional leaders (e.g., Finance, Operations, marketing, HR).

• Lead deep-dive analyses on key questions (e.g., growth opportunities, pricing, retention, marketing ROI, labor productivity, capacity utilization).

• Build and maintain predictive and prescriptive models (e.g., demand forecasting, churn/retention, propensity models, scenario modeling).

• Translate insights into actionable, prioritized recommendations with quantified impact and trade-offs.

• Drive the development of analytics products and tools (e.g., internal apps, APIs, decision-support tools) in partnership with software engineering.

Data, Software Engineering & Architecture

• Own the design and evolution of the analytics platform, including data pipelines, data warehouse, data lake, and BI layers.

• Provide leadership and direction to analytics engineers and software engineers responsible for building and maintaining data and analytics services.

• Set and enforce architecture standards and patterns (e.g., modular, scalable, secure, cloud-native design) to ensure the platform can grow with the business.

• Ensure robust data integration from core systems (ERP, CRM, practice management, HRIS, etc.) into a reliable analytics environment.

• Oversee code quality, release management, and SDLC best practices for analytics applications (version control, CI/CD, testing, documentation).

• Partner with cybersecurity and IT infrastructure teams to ensure security, privacy, and compliance across analytics and data platforms.

Data Governance & Quality

• Establish and enforce data governance standards, including definitions, data quality metrics, and data stewardship across functions.

• Ensure data integrity, consistency, and reliability of key performance indicators (KPIs) used by leadership.

• Drive adoption of single sources of truth for critical business metrics.

• Implement monitoring and alerting to proactively manage data quality and system performance.

• Drive a master data management strategy and implementation.

Business Partnership & Communication

• Act as a trusted partner to functional and market leaders, understanding their strategies and translating them into analytics needs.

• Lead the creation of executive-level presentations that synthesize insights into compelling stories that inform decisions.

• Enable leaders to self-serve insights where appropriate, while providing white-glove support for high-stakes decisions.

• Facilitate cross-functional data and analytics initiatives, ensuring alignment across Finance, Operations, Marketing, HR, and Technology.

Team Leadership & Development

• Build, lead, and mentor a high-performing Data and Analytics team, including data analysts, BI developers, data engineers, data scientists, and visualization experts.

• Design clear roles, career paths, and capabilities for the team (e.g., advanced analytics, visualization, experimentation).

• Foster a culture of curiosity, rigor, and continuous improvement, emphasizing business impact over "analytics for analytics' sake."

• Manage third-party analytics partners and tools as needed.

Tools, Technology & Innovation

• Own the BI and analytics tools roadmap (e.g., Power BI/Tableau, statistical tools, data science platforms).

• Evaluate and implement new analytical methods and technologies (e.g., AI/ML, automation, data storytelling tools) to increase speed, accuracy, and usability.

• Standardize analytics best practices, templates, and methods across the organization.

Qualifications

Education

• Bachelor's degree in Analytics, Statistics, Mathematics, Economics, Finance, Data Science, Computer Science, Engineering or related field required.

• Master's degree (MBA, MS in Analytics / Data Science, or related) strongly preferred.

Experience

• 12+ years of progressive experience in business analytics, data science, business intelligence, or related fields, with at least 5+ years in a senior leadership role.

• Significant experience working with or leading software engineering and/or data engineering teams supporting analytics and data platforms.

• Proven track record leading analytics in a multi-site, complex, or high-growth environment (e.g., healthcare, retail, consumer services, financial services, technology).

• Demonstrated success in partnering with executive leaders and influencing strategic decisions using data.

• Experience standing up or significantly maturing an enterprise analytics function, including governance, tools, and operating model.

• Strong background in financial and operational analytics, including P&L, forecasting, pricing, and performance management.

Technical Skills

• Proficiency with modern BI and visualization tools (e.g., Power BI, Tableau, Looker).

• Hands-on familiarity with data engineering and software engineering concepts and tools, such as:

• SQL and data modeling

• Python development

• Cloud data platforms (e.g., Azure, AWS, GCP)

• ETL tools and orchestration frameworks

• APIs, microservices, and integration patterns

• Version control (e.g., Git), CI/CD, automated testing.

• Understanding of advanced analytics and data science methods (e.g., regression, clustering, forecasting, optimization), with the ability to lead and challenge teams doing this work.

Leadership Skills

• Strategic Thinker: Sees the big picture, anticipates trends, and connects analytics to strategy and long-term value creation.

• Business Athlete: Fluent in P&L, growth, and operational levers; frames insights in financial and strategic terms executives care about.

• Data Storyteller: Translates complex data into clear, concise narratives and recommendations tailored to executive audiences.

• Influential Partner: Builds trust quickly, challenges constructively, and helps leaders make tough, data-backed trade-offs.

• Builder & Operator: Comfortable both designing the future-state analytics function and driving day-to-day execution.

• People Leader: Invests in talent, gives clear direction, and creates a high-accountability, high-support environment.

• Change Agent: Drives adoption of analytics and new ways of working across functions, with patience and persistence.

Success in the First 12 Months Will Look Like

• A clear enterprise analytics strategy and roadmap is defined, socialized, and in motion.

• A standard set of executive dashboards and KPIs is in place and trusted across the organization.

• Analytics has delivered tangible business impact (e.g., revenue uplift, cost reduction, improved productivity) with quantified results.

• Leaders view the Business Analytics team as a critical partner in planning, decision-making, and performance management.

• The analytics team is strong, engaged, and operating with clarity, with defined priorities and ways of working.

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Job Details

Pay Type Salary

Job Category Corporate