Lead Clinical Data Manager at cGxPServe Phoenix, AZ

cGxPServe

Phoenix (AZ)

On-site

USD 120,000 - 140,000

Full time

14 days+

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Job summary

cGxPServe is seeking a Lead Clinical Data Manager in Phoenix, AZ. The successful candidate will plan and manage all data management activities for clinical studies, ensuring high quality and compliance with GCP. The role demands a minimum of 10 years of experience in Clinical Data Management with solid expertise in drug development processes. Excellent communication skills and proficiency in SAS are a must. Join cGxPServe to be part of a dynamic team that values quality and collaboration.

Qualifications

  • Minimum 10 years of experience in Clinical Data Management.
  • Strong data management expertise and knowledge of Good Clinical Practice.
  • Excellent oral and written communication skills.

Responsibilities

  • Plan and drive the conduct of Data Management activities.
  • Manage high complexity studies.
  • Lead the data quality evaluation using visual analytics tools.

Skills

Clinical Data Management
Drug development processes
Data management expertise
Good Clinical Practice (GCP)
Project Management
Analytical skills
Communication skills
SAS System proficiency

Tools

Medidata platform
Electronic Data Capture (EDC) systems

Job description

Lead Clinical Data Manager job at cGxPServe. Phoenix, AZ.

Responsibilities:
  • Plan and drive the conduct of all Data Management activities for assigned project(s) ensuring a consistent approach across studies.
  • 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.
  • 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.
  • Lead the data quality evaluation by investigating all clinical and operational data, evaluating trends, deviations, using visual analytics tools and ad hoc reports.
  • 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)
  • 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).
  • Advanced analytical and technical skills to interrogate and mine high volumes of data from a variety of sources.
Requirements:
  • Minimum 10 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.
  • 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 System.
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