Associate Director, Study Data Services

Job Description

Role Overview:

The Associate Director, Study Data Services leads and develops a programming and reporting team - set goals, assign work, coach performance, and manage recruiting/onboarding - while communicating status and risks to leadership and partners. Provide hands-on technical review, solutioning support, enforce SOPs/standards, manage workload and prioritization, track quality and timelines, and drive best practices (code review, reusable components, test automation) and continuous improvement.

Responsibilities:

Programming and reporting:

• Lead design and deployment of clinical technology system solutions (e.g., for EDC [Electronic Data Capture], RTSM [Randomization and Trial Supply Management], and eCOA/ePRO [electronic Clinical Outcomes Assessment/ electronic Patient-Reported Outcomes]) using programming frameworks and automation tools.
• Provide technical oversight for clinical programming, reporting, and data integration across portfolios.
• Recommend and implement tools to streamline design, build, and validation processes.
• Apply data literacy to design transformation strategies for actionable insights.
• Develop advanced reporting solutions (dashboards, listings, visual analytics) with reusable components and role-based access.

Data Engineering:

• Define and govern integration architecture, including data sources and transformation workflows.
• Ensure consistent implementation of enterprise standards and reusable assets.
• Monitor and troubleshoot data ingestion and consumption for reliability.
• Automate and strengthen data engineering processes to reduce risk and improve efficiency.
• Develop robust data models, semantic layers, and curated datasets; enforce quality checks.

Process:

• Drive process optimization by identifying gaps and implementing improvements.
• Translate strategy into clear priorities, roadmaps, and ways of working for assigned domains.
• Lead testing strategies for solutions; automate validation and ensure traceability.
• Contribute to resource planning and workload distribution across global teams.
• Set documentation and audit standards; ensure compliance through rigorous change management.
• Lead cross-functional collaboration, meetings, and enterprise-level improvement programs.
• Influence adoption of data standards, tools, and automation for better delivery and decision-making.
• Provide leadership, coaching, and mentoring to build capabilities and foster a culture of quality and collaboration.
• Support release management across environments; align stakeholders, lead UAT (User Acceptance Training), and improve reporting standards.
• Partner across teams to turn data and technical findings into clear, actionable recommendations
• Act as a reliable partner to GDMS and other cross-functional teams, actively seeking input, aligning on priorities, and closing feedback loops to drive high-quality, coordinated delivery.

People management:

• Align teams around a clear direction; set clear objectives aligned to organizational goals; assign work and set priorities accounting for work-life balance sustainability.
• Conduct regular check-ins and annual reviews; coach for performance; provide recognition.
• Develop career plans; create growth opportunities and promotion cases; ensure appropriate training and mentoring.
• Coordinate on-shore/off-shore and contingent resources; ensure role clarity and effective handoffs.
• Manage an operating budget and optimize spend against priorities.
• Inspires and ensures that team leaders are effectively supporting and empowering their individual leaders.

Technical skills:

• Expert-level proficiency in different technology languages (e.g., SQL, Python, SAS, and R) for implementing clinical data collectors, integrations, transformations, visualizations
• Evidence of experience in architecting and interoperability of EDC platforms, data integration environments, clinical operations systems, and cloud computing platforms
• Proficiency with key data-management and/or clinical operations tools and platforms (e.g., systems for data capture, review, visualization, reconciliation, and reporting), with the ability to help select, configure, or optimize solutions.
• Broad understanding of the data-management technology ecosystem (e.g., data capture, review, reconciliation, reporting, analytics, and enabling tools) and how components fit together across the end-to-end process.
• Experience leveraging automation, scripting, or digital solutions to streamline data-management activities and reduce manual effort.
• Ability to interpret operational and quality metrics, use analytical/forecasting tools for capacity and scenario planning, and translate insights into clear decisions and actions.
• Strong understanding of common clinical and regulatory data standards, clinical operational data models, metadata management, and controlled terminologies (e.g., MedDRA, WHODrug) to ensure consistency and submission readiness.
• Strong understanding of validation, system lifecycle, data-privacy, and System Development Lifecycle Management activities

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