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Entry Level Clinical Data Management Jobs in Washington

Actalent

Clinical Pharmacist

Washington, DC · On-site

$134K - $160K/yr

... entry-level clinical pharmacist role. In addition to providing direct clinical services, the ... Enter, verify, and maintain accurate computer records and data for medication orders, ensuring ...

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Entry Level Clinical Data Management information

What is entry level clinical data management?

Entry level clinical data management involves collecting, processing, and ensuring the quality and accuracy of data generated during clinical trials. Professionals in this role typically assist in data entry, validation, and preparing reports under the supervision of senior data managers. They play a crucial part in maintaining the integrity of clinical trial data, which is essential for regulatory submissions and the development of new medical treatments. This position is ideal for individuals with a background in life sciences, strong attention to detail, and an interest in clinical research.

What does a typical day look like for someone in entry level clinical data management?

In an entry-level clinical data management position, you can expect to spend your days supporting the collection, review, and validation of clinical trial data. Your responsibilities may include entering data into clinical databases, performing quality checks, resolving data discrepancies, and collaborating closely with clinical research associates and other data managers. You'll also learn industry regulations and work with specialized software tools. This role offers valuable exposure to the clinical research process and provides a strong foundation for advancement within the field.

What are the key skills and qualifications needed to thrive as an entry level clinical data management professional?

To thrive as an Entry Level Clinical Data Management professional, you need a background in life sciences, attention to detail, and a basic understanding of clinical research protocols, often supported by a relevant bachelor’s degree. Familiarity with data management systems like Oracle Clinical or Medidata Rave, and knowledge of Good Clinical Practice (GCP) guidelines or clinical data management certifications, are commonly required. Strong organizational skills, problem-solving ability, and effective communication help you collaborate with cross-functional teams and ensure data quality. These skills and qualities are essential for maintaining data integrity, regulatory compliance, and the successful execution of clinical trials.

What is the difference between Entry Level Clinical Data Management vs Clinical Data Coordinator?

AspectEntry Level Clinical Data ManagementClinical Data Coordinator
CredentialsBachelor's in life sciences or related field; familiarity with data management toolsBachelor's degree; experience with data entry and database management
Work EnvironmentPharmaceutical companies, CROs, clinical research settingsClinical trial sites, research organizations, CROs
Job FocusData entry, validation, database setup, basic analysisData collection, quality checks, database updates
Common Search IntentEntry level data roles in clinical researchData management roles at clinical sites

Entry Level Clinical Data Management involves working with clinical trial data in a research or pharmaceutical setting, focusing on data validation and database setup. Clinical Data Coordinators typically handle data collection and quality checks at trial sites. Both roles require similar educational backgrounds and are essential in clinical research, but they differ in their specific responsibilities and work environments.

What are the most commonly searched types of Clinical Data Management jobs in Washington?

The most popular types of Clinical Data Management jobs in Washington are:

What are popular job titles related to Entry Level Clinical Data Management jobs in Washington?

For Entry Level Clinical Data Management jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Entry Level Clinical Data Management jobs in Washington look for?

The top searched job categories for Entry Level Clinical Data Management jobs in Washington are:

Entry Level Clinical Data Management jobs near you
Infographic showing various Entry Level Clinical Data Management job openings in Washington as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Clinical Data & Applications Analyst II

Choice. Respect. independence. (CRi)

Chantilly, VA

Full-time

Posted 9 days ago

Job description

Clinical Data & Applications Analyst

Position Summary

CRi is seeking a Clinical Data & Applications Analyst to support the management, optimization, and implementation of our clinical technology applications, with a primary focus on our Electronic Health Record (EHR) systems.

This role partners closely with Clinical Leadership, Training, MIS, and other internal and external stakeholders to improve how clinical systems, data, reporting, and emerging technologies are used across the organization. The Clinical Data & Applications Analyst will play an important role in advancing our EHR capabilities, integrating AI-supported documentation processes, improving data quality, and developing efficient technology-enabled workflows.

Key Responsibilities

  • Partner with the Chief Clinical Officer to support the back-end build and design of internal and external reports and compile data required for routine reporting.

  • Support the daily operation, maintenance, configuration, and updates of the organization's EHR software.

  • Develop and implement strategies to improve the organization's use of its EHR and related clinical applications.

  • Ensure AI-generated clinical documentation maps accurately and appropriately into the EHR.

  • Evaluate the effectiveness of AI tools in reducing documentation errors and documentation time.

  • Partner with Training and MIS teams to develop training and support users on EHR and AI-enabled functionality.

  • Maintain data dictionaries and documentation for clinical applications.

  • Create and improve workflows utilizing Microsoft SharePoint and Teams.

  • Conduct audits of clinical systems, data inputs, outputs, and processes to support data integrity and quality.

  • Provide consultation, troubleshooting, and application support as needed.

  • Coordinate with departments across the organization to promote effective communication and interoperability between systems.

  • Assist with research and evaluation of emerging technologies that may improve clinical operations and data management.

  • Prepare user documentation, system guidance, and other technical resources.

  • Perform other duties as assigned.

Knowledge, Skills & Abilities

The successful candidate will bring:

  • Basic literacy and understanding of Artificial Intelligence (AI) and its application within business or clinical environments.

  • Knowledge of interoperability and data exchange between software systems.

  • Knowledge of data administration principles, practices, policies, and standards.

  • Understanding of data definition, modeling, logical design, database design, and quality control.

  • Experience working with data modeling tools and relational databases.

  • Strong analytical skills with the ability to gather, organize, analyze, and communicate data in multiple formats.

  • Strong problem-solving and critical-thinking skills.

  • Ability to research and evaluate new information technologies.

  • Ability to translate complex technical terminology into clear, understandable concepts for non-technical audiences.

  • Strong presentation and communication skills, including the ability to brainstorm, present, discuss, and support recommendations.

  • Ability to work effectively with stakeholders representing different professional perspectives.

  • Strong organizational, project coordination, and prioritization skills.

  • Ability to establish and maintain effective business relationships.

  • Ability to help stakeholders resolve issues involving cross-departmental data sharing, usage conflicts, and data inconsistencies.

  • Ability to develop clear user and system documentation.

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