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Exemption Status:

Exempt

Schedule Details:

Scheduled Hours:

Shift:

1 - Day Shift, 8 Hours (United States of America)

Hours:

40

Cost Center:

99940 - 5950 IS Administration

This position may have a signing bonus available a member of the Recruitment Team will confirm eligibility during the interview process.

Everyone Is a Caregiver

At UMass Memorial Health, everyone is a caregiver – regardless of their title or responsibilities. Exceptional patient care, academic excellence and leading-edge research make UMass Memorial the premier health system of Central Massachusetts, and a place where we can help you build the career you deserve. We are more than 20,000 employees, working together as one health system in a relentless pursuit of healing for our patients, community and each other. And everyone, in their own unique way, plays an important part, every day.

Reporting to the Senior Vice President/Chief Transformation Officer, the Chief Data Officer (CDO) provides enterprise leadership for UMass Memorial Health’s data and analytics strategy, execution, and impact. The CDO leads an integrated data and analytics organization focused on enabling evidence-based decision-making, advancing data literacy, and improving clinical, operational, and strategic performance.

The CDO drives transformation by delivering a modern, scalable data ecosystem including a Unified Data Platform and advancing advanced analytics capabilities such as predictive modeling and AI/ML. As a trusted advisor to executive leadership, the CDO ensures data strategies are aligned with business and clinical priorities and oversee enterprise data architecture, governance, analytics, reporting, and security.

A core responsibility is the development and execution of Enterprise Data Strategy, supported by strong data governance and cross-functional partnerships with IS, clinical, operational, and transformation leaders. The CDO champions modernization of the analytics technology stack and expands access to trusted data through self-service capabilities.

The role requires demonstrated thought leadership and a track record of measurable impact, as well as the ability to build and lead a high-performing team of data engineers, analysts, data scientists, and governance professionals.

Success will be measured by enterprise adoption of analytics, delivery of the Unified Data Platform, measurable performance improvements, and sustained increases in data literacy and decision quality

This role will be expected to achieve specific goals, including:
• Delivery of the Unified Data Platform
• Establishing a unified and trusted enterprise data strategy and governance model.
• Elevating the use of analytics in strategic and operational decisions.
• Leading the adoption of advanced analytics, including AI and machine learning.
• Driving integration and modernization of data platforms, tools, and capabilities.
• Building and developing a cross-functional, high-impact data and analytics team.
• Collaborating with stakeholders to define and prioritize enterprise-wide data initiatives.
• Ensuring robust data governance, security, and compliance practices.
• Fostering a culture of curiosity, innovation, and data fluency across UMMH.

I. Major Responsibilities:

• Lead the development and execution of a unified enterprise data and analytics strategy aligned with organizational objectives, with enterprise authority over data standards, analytics platforms, and governance frameworks.
• Modernize and oversee the enterprise data ecosystem, data warehouses, data lakes, and analytics platforms, and partner closely with Information Services to ensure secure, scalable, and high-performing infrastructure.
• Ensure secure, high-quality data ingestion, integration, and management across clinical, operational, and financial domains to support trusted analytics and insights.
• Establish and lead enterprise data governance, stewardship, and data quality programs in compliance with privacy, security, and regulatory requirements.
• Advance analytics and data science capabilities, including self-service analytics, predictive modeling, population health analytics, and AI-driven decision support, to enable real-time and strategic decision-making.
• Drive continuous i