VP, Chief Data and AI Driven Analytics Officer

Beth Israel Lahey Health•Woburn, MA

1d•$370,000 - $400,000

About The Position

The Vice President, Chief Data and AI Driven Analytics Officer establishes and leads an enterprise-wide capability that uses artificial intelligence as the primary analytics engine to turn clinical, operational, financial, workforce, research, and consumer data into timely insights, predictions, recommendations, and actions. The officer partners with executive, clinical, operational, research, financial, compliance, privacy, security, and technology leaders to define strategy, priorities, governance, investment, and measurable value. The role provides executive leadership for an AI-first analytics ecosystem built on trusted Epic EHR and enterprise data. It advances machine learning, generative AI, natural language processing, intelligent agents, predictive and prescriptive analytics, and decision intelligence embedded in clinical and business workflows. Traditional reports, dashboards, and business intelligence tools are used selectively where appropriate rather than as the primary means of analysis or decision support. The officer aligns the data, AI, and analytics roadmap with organizational strategy and regulatory obligations, ensuring AI-enabled insights are accurate, explainable, equitable, secure, and actionable. The role builds enterprise capabilities through strong data foundations, reusable AI services, responsible AI governance, talent development, product operating models, workflow redesign, change management, vendor oversight, and adoption.

Requirements

Master's degree in Computer Science, Information Systems, Data Science, Analytics, Artificial Intelligence, Business, Healthcare Administration, or a related field; an equivalent combination of education and relevant executive experience may be considered.
Fifteen or more years of progressively responsible experience in healthcare data, analytics, technology, informatics, or related functions.
Seven or more years of leadership experience, including responsibility for enterprise strategy, teams, budgets, governance, and executive stakeholder engagement.
Experience leading data and analytics in a large, complex, multi-entity health system.
Demonstrated expertise in AI-first analytics strategy, enterprise data and AI governance, product operating models, portfolio management, organizational design, workflow transformation, and change leadership.
Executive-level knowledge of healthcare delivery, clinical and revenue-cycle workflows, data privacy and security, interoperability, data quality, model risk, algorithmic bias, and responsible AI practices.
Deep knowledge of Epic EHR data capabilities, enterprise data architecture, cloud and AI platforms, interoperability standards, data engineering, machine learning, generative AI, natural language processing, intelligent agents, model operations, knowledge retrieval, responsible AI, and cybersecurity controls.
Ability to shift analytics from primarily dashboard-based reporting to embedded, predictive, prescriptive, and conversational intelligence.
No licensure or certification is required.

Nice To Haves

Epic analytics certification(s) or proficiency.
Credentials in data governance, cloud, analytics, or responsible AI.
Experience with Epic EHR analytics, enterprise AI platforms, cloud services, advanced analytics, and AI-enabled solutions.
Demonstrated success leading enterprise transformation in complex, regulated environments.
Experience establishing data governance and responsible AI programs, scaling AI products, and measuring clinical and business value.
Coaching and developing others: providing feedback, instruction, and developmental guidance, and planning and supporting individual development.
Driving results: translating strategic priorities into operational reality and aligning accountability, resources, processes, and measurement to achieve sustainable results.
Emotional intelligence: establishing and sustaining trusting relationships and responding effectively within a complex organizational environment.
Leading change: identifying and driving organizational and cultural changes needed to adapt to market demands, technology, and internal initiatives.
Systems thinking and setting healthcare business strategy: establishing long-term business direction while considering clinical and financial data, resources, market drivers, organizational values, technology, and policy.

Responsibilities

Lead the enterprise data and analytics strategy and multiyear roadmap, positioning AI as the primary engine for insights, predictions, recommendations, and workflow actions across clinical and business domains.
Chair enterprise governance for data, AI, intelligent agents, and predictive decision support, including decision rights, data stewardship, use-case intake, risk tiering, human oversight, model approval, and lifecycle accountability.
Direct the development, acquisition, validation, deployment, and monitoring of machine learning, generative AI, natural language processing, predictive and prescriptive models, intelligent agents, and automation, with controls for performance, drift, bias, explainability, privacy, security, and patient safety.
Create an AI-ready data foundation with enterprise standards for data quality, semantic consistency, lineage, metadata, master data, identity management, access, retention, and appropriate use.
Partner with clinical and operational leaders to replace static, retrospective reporting where appropriate with AI-enabled forecasting, anomaly detection, summarization, conversational analysis, recommendations, and embedded decision support within Epic and other workflows.
Define product, value, and portfolio management practices for AI-driven analytics; measure clinical and business outcomes, adoption, model performance, total cost of ownership, vendor performance, and return on investment; and retire solutions that do not meet established thresholds.
Build, develop, and retain multidisciplinary teams across data engineering, architecture, data science, machine learning engineering, AI/ML operations, analytics product management, prompt and knowledge engineering, governance, and adoption.
Ensure compliance with applicable privacy, security, information sharing, records management, research, and health IT requirements in partnership with Legal, Compliance, Privacy, Cybersecurity, and clinical governance.
Manage operating and capital budgets, strategic vendors, contracts, platform performance, and executive communications.
Represent the data and AI-driven analytics function on enterprise committees and with external partners.
Maintain strict adherence to the BILH Confidentiality policy and incorporate BILH Standards of Behavior and Guiding Principles into daily activities.
Comply with BILH policies and departmental expectations; maintain courteous and effective interactions with colleagues and patients; participate in quality improvement activities; and successfully complete Mandatory Education.
Perform other duties as needed or directed.
Maintain required influenza vaccination as a condition of employment.