2026-03-12
Katalyst Healthcares and Life Sciences
San Francisco,CA
Description:
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
EHR data, data collected directly from patients, omics data, other secondary data)
dvanced 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
nalytical, problem-solving skills and ability to take ownership of decision-making
Strong commitment to quality
Excellent oral and written communication and presentation skills
bility 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.
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