Lead Clinical Data Manager

Clinical Data Manager

Responsibilities:

Lead the data quality evaluation by investigating all clinical and operational data, evaluating trends, deviations, using visual analytics tools and ad hoc reports.

Manage high complex studies and support specific activities of studies managed by other data managers or consultants.

Provide technical tutoring and supervise data managers and/or contractors assigned to clinical studies by conducting regular reviews of activity status.

In-depth knowledge of Clinical Data Interchange Standards Consortium (CDISC) relating to data standards including Study Data Tabulation Model (SDTM) and Case Report Tabulation Data Definition Specification (Define.xml).

Manage and guide providers, setting requirements, preparing or reviewing Request for Proposals and monitoring performance.

Regularly monitor data management costs of the assigned studies ensuring respect of budget.

Define and proactively manage risks with potential impact on study systems setup, study conduction, or reliability of study results.

Ensure all data collection systems for assigned projects are setup, tested and fit for purpose according to expectations and timelines.

Define the strategy and lead the preparation of data package for regulatory submission.

Represent data management for auditing and regulatory inspection.

Advanced analytical and technical skills to interrogate and mine high volumes of data from a variety of sources.

Requirements:

Minimum 8+ years of experience in Clinical Data Management in CROs or Pharmaceutical Industry.

Solid knowledge of drug development processes.

Strong data management expertise.

Excellent knowledge of Good Clinical Data practices, GCP and regulatory requirements.

Experience with clinical databases, electronic data capture (EDC) systems, wearables, and sensors to collect data directly from patients.

Excellent knowledge of Risk-Based approach.

Knowledge of Real-World data sources and processes to collect/manage different types of sources.

Basic knowledge of Artificial Intelligence (AI).

Project Management skills.

Excellence in planning and priorities setting.

Analytical, problem-solving skills and ability to take ownership of decision-making.

Strong commitment to quality.

Excellent oral and written communication and presentation skills.

Ability to collaborate and work in a team-based environment.

Courage, resilience, and ability to adjust to a rapidly changing environment.

Experience with Medidata platform.

Familiarity with other platforms for secondary data.

Proficiency in SAS Systems.