Clinical Trial Data Manager – Study Dataset Quality

MNC JOBS INFO; Singapore; Hybrid; SGD 90,000 - 140,000; Full time

Benefits offered by this job

Remote or hybrid work

Professional development

Competitive benefits

Job summary

MNC JOBS INFO is seeking a detail-oriented Clinical Trial Data Manager – Study Dataset Quality to oversee data management, validation, and QA across the trial lifecycle, ensuring datasets are accurate and ready for analysis and regulatory submissions.

You'll collaborate with CRAs, biostatisticians, programmers, and other stakeholders to monitor data quality, manage queries, and support database cleaning and lock activities in a flexible hybrid work environment.

Qualifications

• Bachelor's degree in a life sciences field is required.
• Experience in clinical data management and data validation.
• Familiarity with regulatory requirements (GCP/CDISC) desirable.
• Strong attention to detail and problem solving.
• Excellent written and verbal communication.

Responsibilities

• Manage clinical trial data lifecycle from setup to database lock.
• Develop and maintain CDMPs, data review guidelines, and validation specs.
• Ensure datasets align with study protocols and CRFs.
• Coordinate with teams to maintain accurate participant records.
• Monitor data collection and identify quality issues.

Skills

Attention to detail

Analytical thinking

Data management

Regulatory knowledge

Communication

Education

Bachelor’s degree in Life Sciences, Pharmacy, Biotechnology, Health Informatics, Statistics or related field

Master’s degree in Clinical Data Management or related field (advantage)

Clinical Data Management certification desirable

Tools

Medidata Rave

Oracle Clinical

Veeva systems

SQL

Excel

Job description

1. Job Summary

MNC JOBS INFO is seeking a detail-oriented and analytical Clinical Trial Data Manager – Study Dataset Quality to support the management, validation, and quality assurance of clinical research data throughout the clinical trial lifecycle. The successful candidate will play an important role in ensuring that clinical trial datasets are accurate, complete, consistent, reliable, and suitable for statistical analysis, regulatory submissions, and clinical research reporting.

The Clinical Trial Data Manager will collaborate with clinical research associates, clinical operations teams, biostatisticians, statistical programmers, medical professionals, and other research stakeholders to maintain high-quality study data. The role involves overseeing data collection processes, reviewing electronic data capture (EDC) systems, identifying discrepancies, managing data queries, monitoring data quality metrics, and supporting database cleaning and lock activities.

The ideal candidate will have a strong understanding of clinical data management principles, clinical trial protocols, data validation procedures, and applicable regulatory requirements. This position requires excellent attention to detail, strong problem-solving abilities, effective communication skills, and a commitment to maintaining the integrity and confidentiality of clinical research information.

This opportunity is suitable for professionals interested in clinical research operations, clinical data management, pharmaceutical research, biotechnology, and healthcare data quality. Employment arrangements, including remote or hybrid work, will depend on the specific project and organizational requirements.

2. Key Responsibilities

Clinical Trial Data Management

• Manage clinical trial data throughout the study lifecycle, from study setup and data collection to database cleaning, reconciliation, and final database lock.


• Develop, review, and maintain clinical data management plans, data review guidelines, data validation specifications, and other study documentation.


• Ensure clinical datasets align with approved study protocols, case report forms, data collection requirements, and applicable study standards.


• Coordinate with clinical research teams to maintain accurate, complete, and consistent participant records.


• Monitor data collection activities and identify potential data quality issues that could affect study outcomes or reporting.

Study Dataset Quality Assurance

• Perform routine data quality reviews to identify missing values, duplicate records, inconsistent entries, outliers, and other data anomalies.


• Conduct cross-checks between clinical databases, laboratory results, adverse event records, medication data, and other relevant study information.


• Review data consistency across clinical data sources and support the resolution of discrepancies before database finalization.


• Develop and maintain quality control checks, validation rules, and data review procedures.


• Document data quality findings, investigate recurring issues, and recommend corrective and preventive actions where appropriate.


• Support quality improvement initiatives designed to reduce data errors and improve the reliability of clinical trial datasets.

Data Validation and Query Management

• Create, review, and maintain data validation checks within electronic data capture systems.


• Generate and manage data queries to resolve discrepancies, missing information, and inconsistencies.


• Collaborate with clinical research associates, investigators, and study teams to ensure queries are addressed within established timelines.


• Track outstanding queries and elevate unresolved or critical data issues to the appropriate stakeholders.


• Verify corrected data entries and maintain clear documentation of query resolution activities.

Electronic Data Capture and Database Management

• Support the configuration, testing, and maintenance of clinical trial databases and electronic data capture systems.


• Participate in user acceptance testing, system validation activities, and the review of data entry workflows.


• Ensure data management processes follow approved procedures and applicable electronic record requirements.


• Maintain appropriate documentation of database changes, validation outcomes, and system-related issues.


• Work with technical teams to investigate data transfer problems, system inconsistencies, and data integration challenges.

Regulatory Compliance and Documentation

• Follow applicable Good Clinical Practice (GCP) principles, organizational standard operating procedures, and relevant regulatory requirements.


• Support compliance with data privacy, confidentiality, and information security requirements.


• Maintain complete, accurate, and traceable documentation of data review, validation, query resolution, and database management activities.


• Assist with clinical study audits, inspections, and quality reviews by preparing requested data management records.


• Support adherence to applicable clinical data standards and regulatory submission requirements, including CDISC standards where relevant.

Cross-Functional Collaboration

• Work closely with clinical operations, biostatistics, statistical programming, pharmacovigilance, medical writing, and quality assurance teams.


• Coordinate data reconciliation activities with laboratory vendors, central imaging providers, and other external data sources when applicable.


• Participate in study meetings to discuss data quality issues, project milestones, and database readiness.


• Communicate risks, progress updates, and data management findings to project stakeholders.


• Contribute to process improvement initiatives, knowledge sharing, and the development of consistent data management practices.

3. Required Skills and Qualifications

Educational Qualifications

• Bachelors degree in Life Sciences, Pharmacy, Biotechnology, Bioinformatics, Health Informatics, Statistics, Information Technology, or a related discipline.


• A masters degree in Clinical Research, Clinical Data Management, Biostatistics, Public Health, or a related field is an advantage.


• Relevant training or certification in clinical data management, Good Clinical Practice, or clinical research operations is desirable.

Technical Skills

• Knowledge of clinical trial data management processes and clinical research documentation.


• Familiarity with electronic data capture platforms such as Medidata Rave, Oracle Clinical, Veeva systems, or comparable clinical data management solutions.


• Understanding of clinical database design, data validation, data cleaning, and database lock procedures.


• Experience reviewing clinical datasets, identifying inconsistencies, and resolving data quality issues.


• Familiarity with Microsoft Excel, including data filtering, sorting, lookup functions, pivot tables, and data reconciliation techniques.


• Knowledge of SQL, SAS, Python, or other data analysis tools is beneficial, depending on project requirements.


• Understanding of CDISC standards, including CDASH and SDTM, is desirable.


• Familiarity with electronic records, audit trails, access controls, and data traceability requirements.

Professional Skills

• Excellent attention to detail and a strong commitment to data accuracy.


• Strong analytical, critical-thinking, and problem-solving abilities.


• Ability to investigate complex data discrepancies and determine appropriate resolution steps.


• Clear written and verbal communication skills.


• Strong organizational skills and the ability to manage multiple study activities simultaneously.


• Ability to collaborate effectively with cross-functional teams.


• Good documentation practices and a commitment to maintaining data integrity.


• Willingness to learn new technologies, clinical research standards, and data management procedures.

4. Experience

Entry-Level Candidates: Candidates with relevant academic qualifications, clinical research training, internships, or exposure to clinical data management may be considered for junior opportunities, depending on project requirements.

Mid-Level Professionals: Approximately 2–5 years of experience in clinical data management, clinical trial data review, database cleaning, data validation, or clinical research operations is preferred.

Experienced Professionals: Candidates with substantial experience managing complex clinical studies, leading data quality initiatives, coordinating database lock activities, or supporting regulatory submissions may be considered for senior-level responsibilities.

Experience in pharmaceutical companies, biotechnology organizations, contract research organizations (CROs), hospitals, academic research institutions, or clinical research service providers is advantageous.

Practical experience with EDC systems, clinical data reconciliation, query management, data review plans, and study documentation will be particularly valuable.

Candidates should demonstrate an understanding of how data quality affects patient safety, clinical study reliability, statistical interpretation, and regulatory decision-making.

5. Working Hours

Working hours will depend on the assigned project, client requirements, study timelines, and employment arrangement.

Typical Schedule: Approximately 8 hours per day, 5 days per week.

Full-Time Opportunities: Standard business hours, subject to the applicable office location and project requirements.

Remote or Hybrid Work: May be available for eligible positions, depending on the employers policies and project needs.

Flexible Scheduling: Limited flexibility may be possible when coordinating with international research teams or clinical study stakeholders.

Project Deadlines: Additional coordination or adjusted working hours may occasionally be required during critical milestones, data review cycles, and database lock activities.

Candidates should be comfortable working with deadlines while maintaining accuracy, documentation quality, and compliance with established procedures.

6. Knowledge, Skills, and Abilities

Clinical Research Knowledge

• Understanding of clinical trial phases, study protocols, case report forms, and clinical research workflows.


• Familiarity with participant data collection, clinical assessments, laboratory data, adverse event reporting, and concomitant medication records.


• Understanding of the importance of accurate data in evaluating treatment safety and efficacy.


• Awareness of Good Clinical Practice principles and relevant clinical research regulations.

Data Quality and Analytical Abilities

• Ability to assess datasets for completeness, consistency, accuracy, and logical validity.


• Skill in identifying trends, unusual values, missing information, and conflicting records.


• Ability to interpret data validation reports and prioritize discrepancies according to their potential impact.


• Capability to support root-cause analysis and recommend practical data quality improvements.

Technology and Systems Knowledge

• Ability to work with clinical data management platforms, spreadsheets, databases, and electronic documentation systems.


• Understanding of data cleaning workflows, reconciliation methods, and controlled data access.


• Ability to learn new clinical research applications and follow system-specific procedures.


• Awareness of data standards and structured dataset requirements used in clinical research and regulatory reporting.

Communication and Collaboration

• Ability to explain data discrepancies clearly to clinical and technical stakeholders.


• Strong coordination skills for working with internal teams and external research partners.


• Ability to maintain professional communication when following up on outstanding queries.


• Willingness to contribute to team objectives and share knowledge with colleagues.

Professional Integrity

• Commitment to confidentiality, ethical research practices, and responsible handling of sensitive clinical information.


• Ability to maintain accurate records and follow approved procedures.


• Sound judgment when identifying potential data risks and escalating issues.


• A proactive approach to learning, continuous improvement, and quality assurance.

7. Benefits

• Eligible employees may receive benefits according to the applicable employment agreement, company policies, and local regulations. Potential benefits may include:


• Competitive salary aligned with qualifications, relevant experience, and job responsibilities.


• Opportunities to work on clinical research projects across therapeutic areas.


• Professional development through clinical data management training and relevant industry certifications.


• Exposure to electronic data capture platforms, clinical research technologies, and data quality methodologies.


• Opportunities to collaborate with experienced professionals in clinical operations, biostatistics, and statistical programming.


• Potential access to remote or hybrid working arrangements for eligible roles.


• Opportunities for career progression into senior clinical data management, data standards, clinical database management, or clinical data operations.


• A professional environment that values accuracy, accountability, collaboration, and continuous improvement.


• Eligible leave, health coverage, retirement benefits, and other employment benefits where provided under the applicable company policy.


• Specific compensation, benefits, and work arrangements should be confirmed in the official employment offer.

8. Why Join MNC JOBS INFO?

Joining an opportunity advertised through MNC JOBS INFO can be a valuable step for professionals who want to develop their careers in clinical research data management and healthcare analytics.

Contribute to Meaningful Research: Help maintain the quality and reliability of clinical trial datasets that support the evaluation of investigational treatments and medical interventions.

Develop Specialized Expertise: Build practical knowledge of clinical data cleaning, database management, data validation, reconciliation, and quality control processes.

Work Across Research Functions: Gain exposure to collaboration between clinical operations, biostatistics, statistical programming, quality assurance, and other clinical research disciplines.

Strengthen Your Technical Skills: Develop your understanding of EDC platforms, data review tools, clinical data standards, and structured research datasets.

Build Long-Term Career Opportunities: Prepare for potential career progression into clinical data management leadership, clinical data standards, clinical database administration, and related research operations roles.

Make Quality a Priority: Apply analytical thinking and attention to detail to help improve data consistency, research documentation, and study readiness.

MNC JOBS INFO should be understood as the company or recruiting name provided for this job description. Candidates should verify the actual employing organization, job availability, compensation, and employment terms before accepting an offer.