We are seeking a detail-oriented and analytical Clinical Data Analyst to support the collection, management, cleaning, and reporting of clinical trial and healthcare data. In this role, you will bridge the gap between clinical operations, data management, and biostatistics to ensure data integrity, protocol compliance, and accuracy across clinical studies.
Core Responsibilities
- Data Management & Cleaning: Review, clean, and validate clinical trial data in Clinical Data Management Systems (CDMS/EDC). Identify data discrepancies, issue queries, and track resolutions.
- Database Design & Testing: Participate in User Acceptance Testing (UAT), electronic Case Report Form (eCRF) design, and implementation of data validation checks in accordance with clinical study protocols.
- Statistical & Analytics Support: Perform exploratory data analysis and generate routine summary reports, dashboards, and visualizations using tools like SQL, SAS, R, or Python to monitor study progress and safety trends.
- Regulatory & Protocol Compliance: Ensure data collection and handling adhere to Good Clinical Practice (GCP), CDISC standards (SDTM/ADaM), HIPAA, and regulatory guidelines (FDA/EMA).
- Cross-Functional Collaboration: Partner with Clinical Research Associates (CRAs), Data Managers, Biostatisticians, and Medical Monitors to ensure timely database lock and data deliverables.
Qualifications
- Education: Bachelor’s or Master’s degree in Health Informatics, Biostatistics, Data Science, Life Sciences, or a related quantitative field (Required).
- Experience: 0–5 years of experience in clinical data management, clinical analytics, healthcare research, or CRO environments.
- Skills (Required):
- Strong analytical and data-driven problem-solving skills.
- Proficiency in SQL and database query writing.
- Hands-on experience with Electronic Data Capture (EDC) systems (e.g., Medidata Rave, REDCap, Oracle InForm).
- Knowledge of clinical trial processes, medical terminology, and GCP standards.
- Excellent written and verbal communication skills for cross-functional reporting.
- Preferred Skills:
- Familiarity with statistical programming languages (SAS, R, or Python) and data visualization tools (Tableau, Power BI).
- Knowledge of CDISC data standards (SDTM/ADaM).
- Basic understanding of clinical database programming or validation logic.