Senior Director, Data Management Systems

Organizational Overview:

Immunovant, Inc. is a clinical-stage immunology company dedicated to enabling normal lives for people with autoimmune diseases. As trailblazer in anti-FcRn technology, the Company is developing innovative, targeted therapies to meet the complex and variable needs of people with autoimmune diseases.

The Role:

Reporting to the Vice President, Data Management, this position is responsible for providing strategic and operational leadership over the clinical data technology ecosystem, including eCOA/ePRO platforms, eDiary solutions, Medidata Rave (EDC), and Elluminate. This role is not directly responsible for hands-on clinical data management activities (e.g., data cleaning, query resolution, database lock); rather, it requires a strong clinical data management background to inform sound systems strategy, oversee system governance, and lead a team responsible for platform architecture, configuration, integration, and lifecycle management. The ideal candidate understands data management processes deeply enough to translate them into scalable, well-governed technology solutions, and brings proven experience leading systems teams. Serves as a key member of the Data Management Leadership Team, supporting cross-functional team needs and oversees the management of system related enhancements to support study deliverables. Interfaces with CROs and is responsible for managing internal Data Management team members.

Key Responsibilities: 

 Leadership & Management

• Lead, mentor, and develop a team of clinical trial solutions personnel
• Set systems strategy, roadmap, and performance metrics; conduct performance reviews and support career development.
• Manage systems related budget, resourcing, vendor contracts, and staffing plans across concurrent systems and study portfolios.
• Serve as a key member of the clinical data management leadership team, representing clinical systems in cross-functional governance forums.
• Partner with (but do not directly own) the data management operations team and vendors, ensuring systems strategy aligns with DM process needs.

Clinical Systems Strategy & Governance

• Own the enterprise strategy, roadmap, and governance model for core clinical data systems, including:
• eCOA / ePRO platforms (patient/clinician-reported outcomes)
• eDiary systems
• Medidata Rave EDC
• Elluminate (data review, aggregation, and analytics platform)
• Define and maintain system governance frameworks: access management, role-based permissions, change control, and version control across platforms.
• Establish standards for system configuration, study build templates, and reusable libraries to drive consistency and efficiency across studies.
• Lead vendor management and contract oversight for all clinical systems vendors, including SLA definition, performance monitoring, and renewal/negotiation strategy.
• Own system-related budget planning, licensing decisions, and total cost of ownership analysis.

System Implementation & Lifecycle Management

• Lead selection, evaluation, and implementation of new clinical systems and platform upgrades, including RFP processes and vendor due diligence.
• Oversee computer system validation (CSV/CSA) activities, ensuring systems meet 21 CFR Part 11, GxP, and data integrity requirements.
• Direct system configuration, build, and testing activities for EDC, eCOA, eDiary, and Elluminate environments.
• Manage the end-to-end lifecycle of clinical systems: onboarding, ongoing maintenance, periodic review, upgrades, and decommissioning/retirement/data archival.
• Establish and maintain disaster recovery, business continuity, and system uptime/performance standards in partnership with IT.

Integration & Interoperability

• Lead architecture and oversight of system integrations (e.g., EDC-to-eCOA, EDC-to-Elluminate, EDC-to-IRT/RTSM/safety databases) to ensure seamless, accurate, and timely data flow.
• Partner with IT/technical teams to define data integration specifications, API/interface requirements, and data mapping standards.
• Troubleshoot and resolve systemic/integration-level issues, distinguishing systems-level root causes from data management process issues.
• Drive adoption of autom