Vice President

CO Salary Range: USD 200,000.00 - 292,000.00 per year

Posting Date
01/26/2026

2000 16th Street, Denver, Colorado, 80202, United States of America

DaVita is currently recruiting for a Vice President of Clinical Analytics - a newly created position based in Denver, CO.

General Purpose of the Job

This executive leadership position is responsible for transforming DaVita's clinical data, reporting and analytics functions. The Vice President will lead the strategy and execution for clinical data and analytics across our DaVita Kidney Care ("DKC") and Integrated Kidney Care ("IKC") teams, providing comprehensive and actionable clinical, operational, and financial information to key stakeholders.

Supervisory Responsibilities

• Talent Strategy & Development: Define and execute a talent strategy to recruit, retain, and develop world-class analytics engineers and business intelligence specialists.
• Organizational Design: Design and evolve a highly effective organizational structure (aligned to the hub-and-spoke model) with clear leveling, career paths, and focused domain/functional teams (e.g., DKC, IKC OR Data Domain).
• Team Efficiency & Velocity: Drive operational efficiencies within the team by streamlining workflows, standardizing best practices (e.g., UAT, reports deployment), and minimizing "data wrangling" time.
• Professional Growth: Champion growth opportunities to elevate the technical of the analytics team. Outline and support growth of team members for analytics and BI career ladder.
• Culture of Insight: Foster an insights-first culture that promotes intellectual curiosity, challenges assumptions, and embeds data-driven decision-making across the business.
• Executive Translation: Serve as the executive translator between complex analytical outputs and C-suite strategy, ensuring insights are communicated clearly and tied directly to business outcomes.

• Intake & Prioritization: Establish a transparent, centralized intake process and governance body to evaluate, prioritize, and manage the portfolio of analytics projects based on strategic value and return on investment (ROI).
• Roadmap and Portfolio Management: Maintain a high-level, clear quarterly and yearly roadmap view of all analytics initiatives, communicating delivery timelines, dependencies, and business impact to executive stakeholders.
• Product Management & Adoption: Implement strong product management principles for all analytical assets (e.g., dashboards, models) to actively measure user adoption, frequency of usage, and overall satisfaction, driving continuous improvement.
• Service Level Agreements (SLAs): Define and enforce clear Service Level Agreements (SLAs) with business stakeholders for key deliverables, including reporting availability, model refresh rates, and time-to-insight for new requests.
• Capacity Planning & Productivity: Implement rigorous metrics and tools for measuring team capacity, utilization, and productivity, ensuring resources are optimally allocated and mitigating burnout risks.
• Requirement Definition (SMEs): Establish a formal, repeatable process for partnering with key Business Subject Matter Experts (SMEs) to deeply define analytical requirements, validate hypothesis, and co-create impactful business insights.
• Model Governance: Oversee the governance framework for analytical models, ensuring compliance, ethical use, documentation, and a clear path for model monitoring and deprecation.
• Support, Operations, & Value Tracking: Direct the support and operations function to proactively monitor and resolve analytical issues, ensure platform uptime, and systematically track and report on the tangible business value (e.g., revenue increase, cost reduction) generated by insights.

• Tool Rationalization & Modernization: Lead the rationalization and modernization of the analytics technology stack (BI, visualization, data science platforms) to reduce redundancy, optimize licensing costs, and improve team efficiency.
• Data Product Consumption: Mandate and ensure the analytics team effectively leverages the "Gold Layer" (curated, governed) assets and data products delivered by the central Data Management Hub, maximizing the ROI of central data efforts.
• AI for Acceleration: Strategically implement Artificial Intelligence (AI) and Machine Learning (ML) techniques to accelerate internal analytics workflows, such as automated report generation, anomaly detection in data quality, and model tuning.
• GenAI for End Users: Pilot and implement Generative AI tools (e.g., natural language querying) to aid end users, empowering self-help capabilities and democratizing access to data insights across the organization.

• Team Culture: Actively drive and maintain a high-performing, inclusive team culture that upholds core company values and promotes engagement, collaboration, and a sense of shared purpose and "Fun."
• Strategic Vision & Alignment: Translate the overall business strategy and corporate objectives into a clear, compelling, and actionable multi-year strategy for analytics and insights delivery.
• Executive Stakeholder Management: Proactively manage and influence C-level and senior business leaders, ensuring analytical priorities remain aligned with evolving strategic goals and effectively managing expectations across the portfolio of work.
• Hub-and-Spoke Partnership (Data Management): Build and foster an exceptional, proactive working relationship with the central Data Management and Data Engineering teams to ensure the spoke teams receive high-quality, governed data products and influence the design of the core data platform for analytical needs.
• Change Management & Advocacy: Champion organizational change required to embed new analytical capabilities and promote high data literacy, driving the necessary cultural shift toward insights-driven decision-making.
• Accountability & Ethical Governance: Own the accountability for the quality, integrity, and ethical use of all models, reports, and insights delivered by the analytics teams, ensuring full compliance with internal standards and external regulations.

• Bachelor's degree in a related field such as Data Science, Analytics, Health Informatics, Finance, or Business Administration is required; a Master's degree is preferred.
• Extensive experience in a senior leadership role overseeing data analytics, business intelligence, or a related field, preferably within the healthcare or value-based care industry.
• Proven track record of developing and implementing successful data and analytics strategies that drive business and clinical outcomes.
• Strong experience with modern data technologies, AI/machine learning applications, and business intelligence platforms.
• Demonstrated ability to lead, mentor, and develop large, high-performing teams.
• Excellent communication and stakeholder management skills, with the ability to convey complex data concepts to a non-technical audience.
• Commitment to and role model of DaVita's core values: Service Excellence, Integrity, Team, Continuous Improvement, Accountability, Fulfillment, and Fun.

• Comprehensive benefits: Medical, dental, vision, 401(k) match, paid time off, PTO cash out
• Support for you and your family: Family resources, EAP counseling sessions, access Headspace®, backup child and elder care, maternity/paternity leave and more

• Professional development programs: DaVita offers a variety of programs to help strong performers grow within their career and also offers on-demand virtual leadership and development courses through DaVita's online training platform StarLearning.