Clinical Data Management Specialist II

The Data Manager will ensure that all data are acquired, curated, documented, analyzed, deposited, and shared in accordance with the highest Open Science standards. The Data Manager will serve as the primary bridge between researchers on the site team and the Data Coordinating Center (DCC), the Clinical Coordinating Center (CCC), the study sponsor’s data team, and long‑term data repositories and analytics platforms, ensuring that the project’s data are robust for analysis by the consortium and disseminated for broad reuse by the global scientific community.

• Workflow Development: Collaborate with LNHS stakeholders to follow and maintain scalable, robust Standard Operating Procedures, Data Transfer Plans, and Workflows for data acquisition, organization, storage, curation, metadata capture, and transfer to the DCC in accordance with FAIR (Findable, Accessible, Interoperable, Reusable) data principles and in harmonization with other sites.

• Strategic Planning: In collaboration with LNHS stakeholders, ensure Data Transfer Plan(s) are followed and implemented for all site data, in line with the consortium’s open science frameworks and data‑sharing goals.

• Technical Environment and Tooling: In collaboration with LNHS stakeholders, ensure the project’s data meets capture and upload timelines, initial QC thresholds, version control, detailed metadata documentation, and cloud integration. Ensure alignment with a data transfer policy, and prioritize automation and reproducibility for computational pipelines.

• Analysis Pipelines: As needed and in collaboration with LNHS stakeholders, ensure site alignment with DCC‑centralized analysis pipelines, computational models, and standardized processing tools.

• Quality Assurance: Evaluate the scientific rigor and impact of the team’s data and provide regular progress reports to LNHS stakeholders and programmatic leadership. Investigate and resolve site‑specific quality concerns raised by LNHS stakeholders.

• Liaison Role: Serve as the primary point of contact between the research team and technical partners from project initiation through data release.

• Dataset Tracking: Ensure that status, timelines, and readiness levels are updated regularly and communicated with technical partners and consortium staff.

• Contributor Coordination: Identify and support "dataset contributors" within the team to ensure the submission of complete, accurate datasets and high‑quality metadata.

• Handoff Management: Coordinate the upload and/or transfer of data to the DCC and manage and communicate the reciprocal return of processed or harmonized data back to the local research team. Maintain communication during processing, harmonization, and quality control until datasets are finalized for further release to a long‑term data repository and/or the public.

• Schema
  
  Collaboration:
  
  Work collaboratively with the CCC and DCC to shape metadata standards applicable across the international network, and collaborate with scientists to ensure comprehensive metadata capture throughout the data lifecycle.

• Standards & SOPs: Ensure site alignment with documentation and processes established by the DCC, including standard operating procedures (SOPs), data dictionaries, metadata templates, and README files.

• Team Support: Provide daily training and guidance to team members on data collection SOPs, open science best practices, and data organization.

• Reporting: Track analysis plans and evaluate the impact of generated data to provide regular reporting to study sponsor staff via the annual Project Progress Report and programmatic leadership. Promptly notify relevant parties of identified roadblocks that will impede data collection, analysis, or deposition.

• Working and Interest Groups: Optionally participate in international working groups (deliverable‑oriented and time‑locked) and interest groups (ongoing, topic‑based) to provide visibility into team workflows and identify collaboration opportunities across the network.

• Working Meetings: Participate in regularly scheduled Data…