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Clinical data manager skills for your resume and career

Updated January 8, 2025
5 min read
Below we've compiled a list of the most critical clinical data manager skills. We ranked the top skills for clinical data managers based on the percentage of resumes they appeared on. For example, 12.5% of clinical data manager resumes contained patients as a skill. Continue reading to find out what skills a clinical data manager needs to be successful in the workplace.

15 clinical data manager skills for your resume and career

1. Patients

Here's how clinical data managers use patients:
  • Reconciled study assessments to determine patients' tumor response to medication.
  • Monitored patients on experimental FDA approved cancer treatments.

2. Data Collection

Data collection means to analyze and collect all the necessary information. It helps in carrying out research and in storing important and necessary information. The most important goal of data collection is to gather the information that is rich and accurate for statistical analysis.

Here's how clinical data managers use data collection:
  • Instituted data collection and retention practices for study documents, including informed consent and authorization forms.
  • Led data collection and data clean-up activities including ongoing site management for issue resolution.

3. Data Management

The administrative process that involves collecting and keeping the data safely and cost-effectively is called data management. Data management is a growing field as companies rely on it to store their intangible assets securely to create value. Efficient data management helps a company use the data to make better business decisions.

Here's how clinical data managers use data management:
  • Supported business development for data management time and cost estimates and prepare and present to potential clients on data management capabilities.
  • Established data management group by transitioning from a hired contractor to develop and implement the departments internal systems and procedures.

4. CRF

CRF (Chronic Renal Failure) is a long-term condition where the kidney gradually stops functioning. It's the leading cause of other medical conditions like diabetes, cardiovascular diseases, or high blood pressure.

Here's how clinical data managers use crf:
  • Reviewed CRF completion guidelines, monitoring plans and clinical monitoring reports for accuracy and completeness.
  • Ensured timely ongoing quality management of clinical trial data by identifying inconsistencies in CRF data.

5. QC

Quality control is a set of instructions or procedures to ensure a manufactured product or a service is up to the highest quality standards. This set of quality control criteria are either defined by the clients or the company itself.

Here's how clinical data managers use qc:
  • Review and Resolve listings of errors/inconsistencies identified during QC.
  • Executed Soft Lock and Hard Lock of the database at the completion of the study after rigorous QC of data.

6. Database Development

Here's how clinical data managers use database development:
  • Work closely with clinical database programmers to provide specifications at the time of study database development.
  • Managed the initiation of database development for Scientific Consortia repository with UC -

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7. GCP

Google Cloud Platform (GCP) is a collection of cloud computing services that allow users to develop, deploy, and operate original applications on the web. GCP carries a cloud computing infrastructure that facilitates it in keeping track of the resources (e.g., storage, processing speed, and power, network connectivity, database queries, etc.) of an application or a website, whenever it is run on the cloud platform.

Here's how clinical data managers use gcp:
  • Execute and coordinate daily clinical research activities according to CRA's, SOP's, and GCP's, NIH/ICH guidelines.
  • Reviewed data from a type II diabetes trial to verify adherence to study protocol and ICH GCP.

8. Pharmaceutical Industry

Here's how clinical data managers use pharmaceutical industry:
  • Implemented the knowledge of pharmaceutical industry, and insights on drug discovery and their therapeutic effects.

9. Study Start-Up

A study-start up serves as the foundation of every clinical study, and it helps determine the success of every project. The study start-up is also the stage where the clinical data manager negotiates with sponsors and other business partners, developing comprehensive plans for the study.

Here's how clinical data managers use study start-up:
  • Performed all Data Management (Study Start-Up through Database Lock) including development/implementation of the Data Management Plan.
  • Lead clinical data management process for individual clinical trials from study start-up through archival.

10. Electronic Data Capture

Electronic data capture is the process of gathering data using special computer programs and systems.

Here's how clinical data managers use electronic data capture:
  • Train Clinical research sites on project specific Electronic Data Capture (EDC) system for EDC studies.
  • Gained Electronic Data Capture (EDC) knowledge via Study set-up in ORACLE Clinical RDC.

11. SAS

SAS stands for Statistical Analysis System which is a Statistical Software designed by SAS institute. This software enables users to perform advanced analytics and queries related to data analytics and predictive analysis. It can retrieve data from different sources and perform statistical analysis on it.

Here's how clinical data managers use sas:
  • Developed SAS programs to perform data clean activities including data review and query generation and integration.
  • Participated in the Data Validation process using SAS programs and ensured accuracy and completeness.

12. Completion Guidelines

Here's how clinical data managers use completion guidelines:
  • Developed universal template for OCRDC Forms Completion Guidelines.
  • Designed paper Case Report Forms, Case Report Form Completion Guidelines, subject diaries and source documentation for each clinical trial.

13. ICH

Here's how clinical data managers use ich:
  • Worked on many aspects of data handling in compliance with European, ICH and FDA standards.
  • Participated in departmental initiatives to develop and implement quality standards harmonized according to current regulatory indictors, particularly ICH directives.

14. Data Validation

Data validation is the process of reviewing and arranging data for efficient data analysis. Data validation includes checking data accuracy, quality of data source, and identifying the importance or relevance of the data.

Here's how clinical data managers use data validation:
  • Created and maintained study documentation, created and edited data validation specifications, conducted user acceptance testing of the database.
  • Established protocol-specific data reviews and entry guidelines to document data validation and formatting procedures.

15. CRO

A CRO (Cathode Ray Oscilloscope) refers to an electrical device usually used in a laboratory to exhibit, measure, and analyze different waveforms of electrical circuits.


CRO may also refer to Conversion Rate Optimization -- the practice of improving a process or product to maximize the number of conversions or sales.

Here's how clinical data managers use cro:
  • Coordinate and involve in the training of internal team, CRA's, CRO and vendors based on the project requirements.
  • Prepare, review, and submit clinical data and documents to Clinical Research Organizations (CRO) for quality assurance monitoring.
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List of clinical data manager skills to add to your resume

The most important skills for a clinical data manager resume and required skills for a clinical data manager to have include:

  • Patients
  • Data Collection
  • Data Management
  • CRF
  • QC
  • Database Development
  • GCP
  • Pharmaceutical Industry
  • Study Start-Up
  • Electronic Data Capture
  • SAS
  • Completion Guidelines
  • ICH
  • Data Validation
  • CRO
  • Database Lock
  • Data Management Plan
  • Data Quality
  • Database Design
  • FDA
  • ECG
  • Clinical Operations
  • Clinical Trial Data
  • Data Issues
  • UAT
  • User Acceptance
  • Oncology
  • Edit Check Specifications
  • CDM
  • Clinical Studies
  • MedDRA
  • Data Analysis
  • Medidata Rave
  • SQL
  • Team Training
  • IV
  • Oracle Clinical
  • External Vendors
  • Close Liaison
  • Discrepancy Management
  • Data Entry Guidelines
  • Data Queries
  • Phase II
  • Clinical Trial Management
  • QA
  • Patient Data
  • Manage Timelines
  • Macro

Updated January 8, 2025

Zippia Research Team
Zippia Team

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

Updated January 8, 2025

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