Manager Clinical Data Operations

Role Summary

The Manager, Clinical Data Operations will lead the development and delivery of clinical data visualization solutions to support high-quality clinical trial execution across clinical development programs. This role is responsible for leveraging data from the Scientific Data Lake to create a unified ecosystem of participant-level data visualizations, data quality oversight, external data reconciliation insights, operational and site performance intelligence, audit trail insights, database-lock readiness indicators, and other KPI metrics. The incumbent will enable a data-driven and actionable insights framework aimed at enhancing business capabilities, improving operational efficiencies and oversight, and accelerating decision-making. The ideal candidate will work closely with cross-functional teams to ensure that the clinical data visualization solutions meet the business needs, align with the departmental goals, and adhere to regulatory and compliance standards.

Responsibilities

• Lead the design and development of clinical data visualization solutions that support participant-level tracking, data quality oversight, operational and site performance insights, audit trail insights, database-lock indicators, and other KPI metrics.
• Ensure that the analytical and visualization solutions provide actionable insights to improve clinical data oversight, facilitate efficient data cleaning and review, monitor operational performance, enable improved visibility and decision-making.
• Engage with cross-functional stakeholders to understand the data needs, define requirements, develop specifications, design and deliver solutions that enhance transparency, efficiency, and operational performance.
• Facilitate alignment between technical teams and business partners to ensure requirements are transformed into scalable, long-term data visualization capabilities.
• Manage the lifecycle of analytical and data visualization solutions from proof-of-concept and requirements gathering through testing, deployment, and continuous improvement.
• Source and integrate data from the Scientific Data Lake, ensuring data quality, consistency, and alignment with business requirements.
• Collaborate with the Scientific Data Lake Operations team to optimize data pipelines, metadata management, and ensure seamless access to required datasets.
• Develop and maintain robust clinical data visualization solutions to provide real-time visibility into study progress and performance and fulfill critical study milestones and priorities to accelerate clinical study execution and improve oversight.
• Deliver operational insights to identify risks, bottlenecks, and opportunities to drive process improvements and optimization initiatives.
• Ensure all data insight and visualization workflows comply with GCP, ICH, GDPR, SOPs, and regulatory expectations.
• Drive adherence to data governance principles to safeguard and maintain the security, privacy, and integrity of clinical data.
• Stay updated on emerging technologies and tools in data visualization and analytics to enhance business capabilities.
• Drive the adoption of innovative solutions to improve the efficiency and scalability of clinical data visualization solutions.
• Provide leadership and guidance to junior team members engaged in the development of clinical data visualization solutions.
• Foster a culture of collaboration, innovation, and continuous improvement within the Clinical Data Operations team.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Life Sciences, or a related field.
• 7+ years of experience in clinical data, data visualization, or related disciplines, with a strong background in creating interactive reporting solutions, KPIs, and metrics to support clinical trial oversight.
• Proficiency in data visualization tools such as Tableau, Power BI, or Spotfire.
• Experience with optimization and maintenance of data pipelines, workflow automation, data quality standards, and strong understanding of data lifecycle management in a regulated environment.
• Strong understanding of clinical trial processes, clinical data standards (e.g., CDISC), and regulatory requirements (e.g., GCP, GDPR, HIPAA).
• Experience with data lakes, data pipelines, data integration, automation, and analytics in a clinical research environment.
• Excellent communication and stakeholder management skills.