VP, Head of Data & Analytics

Location: US/CANADA/UK

Job Summary

The VP, Head of Data & Analytics will own the strategy, governance, architecture, and operational execution of data across OPEN Health. This role is responsible for establishing the company’s enterprise data capability and creating the foundational data backbone required to support scalable AI, analytics, operational reporting, client solutions, and the technology-enabled offerings that underpin OPEN Health’s commercial growth ambitions.

This individual will partner across Technology, AI Engineering, Operations, Medical Communications, Commercial, and Business Leadership teams to define how data is structured, governed, integrated, and leveraged throughout the organization. A central focus will be enabling an internal intelligence layer for our commercial and delivery teams: a connected data environment that indexes the firm’s work product, static knowledge assets, project and engagement data, employee expertise, and curated external sources spanning therapy areas, drug and therapy science, and competitive research. The data tier this role designs and builds is what makes that intelligence layer, and the broader AI agenda, possible.

A key focus of the role will be moving OPEN Health from fragmented and siloed data practices toward a more unified and reusable enterprise data ecosystem capable of supporting automation, AI enablement, operational insights, and scalable product development. The role will increasingly think and operate in terms of data assets, with clearly defined consumers, ownership, service expectations, and reuse across the organization.

This is both a strategic and execution-focused leadership role. In the early stages, the successful candidate will be expected to operate hands-on while helping establish the long-term operating model, roadmap, governance framework, and future team structure for data across the organization.

Essential Duties & Responsibilities

• Define and lead OPEN Health’s enterprise data strategy, aligned to the company’s broader technology, AI, and commercial growth ambitions.
• Establish a scalable and AI-ready data ecosystem that supports analytics, automation, operational intelligence, workflow optimization, and technology-enabled offerings.
• Design and stand up the data foundations for an internal commercial intelligence capability, integrating internal work product, knowledge assets, project and engagement data, expertise signals, and curated external sources covering therapy areas, scientific developments, and competitive landscape.
• Lead the design and evolution of enterprise data architecture, integration patterns, governance frameworks, and reusable data services and data products with defined consumers, ownership, and service expectations.
• Drive the delivery and ongoing evolution of data products that provide measurable value to commercial, delivery, and back-office stakeholders.
• Develop standards for data ownership, quality, lineage, lifecycle management, retention, classification, and accessibility across the organization.
• Build foundational data capabilities that support scalable AI adoption, including structured and unstructured data readiness, retrieval systems, automation workflows, and intelligent applications.
• Partner closely with Technology, AI Engineering and AI Innovation, Operations, Commercial, Finance, and Practice teams to improve data consistency, accessibility, interoperability, and reporting capabilities across systems and workflows.
• Work in close collaboration with AI Engineering and AI Innovation to ensure data foundations are aligned to current and emerging AI use cases, including retrieval, agentic workflows, and intelligent applications.
• Help establish a connected enterprise data backbone that reduces fragmentation and enables reusable operational, commercial, and client-facing capabilities, including longer-term opportunities to enrich product platforms and client-delivered solutions.
• Lead discussions and guidance related to data governance, privacy, and regulatory considerations, including HIPAA, GDPR, PHI handling, client contractual obligations, and broader enterprise data risk management practices.
• Partner with IT, Security, Compliance, Risk, and client stakeholders to ensure data practices align with internal policies, regulatory expectations, and client requirements.
• Define practical governance approaches that balance innovation, usability, security, and operational efficiency.
• Support operational and management reporting needs by helping standardize data models and improve reporting structures across finance and back-office functions.
• Identify opportunities to create differentiated and reusable data assets that strengthen OPEN Health’s commercial, AI, and technology capabilities.
• Establish scalable processes, standards, documentation, and best practices for data management across the organization.
• Help define the future operating model and organizational structure for enterprise data capabilities at OPEN Health.
• Build business cases and investment recommendations for future data engineering, governance, analytics, and architecture resources.
• Operate as both a strategic leader and a hands-on technical contributor, particularly during the early stages of building the enterprise data capability.
• Be prepared to directly support data architecture, integration design, governance implementation, data modeling, platform evaluation, and solution delivery activities where needed.
• Work closely with Solution Architecture, AI Engineering, and broader engineering leadership in a highly collaborative and execution-oriented operating model, contributing directly to technical problem solving and implementation efforts.
• Serve as a key advisor and cross-functional leader for enterprise data strategy, governance, and AI enablement initiatives.

Experience, Skills, and Qualifications

• 10+ years of experience in data strategy, data engineering, data architecture, analytics, or enterprise data leadership roles.
• Extensive experience designing and implementing enterprise-scale data solutions and architectures, with hands-on knowledge of modern COTS platforms such as Databricks, Microsoft Fabric, Informatica, or equivalent technologies to support strategic build versus buy decisions.
• Experience establishing or maturing data governance and operational data practices.
• Strong understanding of modern cloud-based data platforms and integration approaches.
• Experience supporting AI, analytics, or automation initiatives through scalable data architecture.
• Experience working across both structured and unstructured data environments.
• Familiarity with data product approaches, including defining consumers, ownership, and service expectations for shared data assets.
• Strong understanding of data quality, governance, security, and lifecycle management principles.
• Ability to operate strategically while remaining hands-on where needed.
• Strong stakeholder management and communication skills across technical and non-technical audiences.
• Experience working within healthcare, pharmaceutical, medical communications, or regulated industries preferred.
• Experience with modern cloud-based data and AI ecosystems preferred.
• Experience working in matrixed and fast-paced delivery environments.

Travel Requirements

• Limited travel as needed for key meetings, workshops, and team collaboration.