Job Summary

The Data Scientist / Data Manager will be responsible for the design, management, analysis, and governance of clinical and research data within the hospital. The role supports clinical research studies, registries, observational cohorts, and trials by ensuring high-quality, compliant, and analyzable data. The position bridges clinical teams, researchers, and IT to transform data into actionable scientific and operational insights.

Key Responsibilities

1. Data Management & Governance

• Design and oversee data collection frameworks for clinical research studies, registries, and databases
• Develop and maintain data dictionaries, metadata, case report forms (CRFs), and standard operating procedures (SOPs)
• Ensure data quality, integrity, version control, and audit readiness
• Manage secure storage, access control, anonymization, and de-identification of patient data

2. Data Analysis & Modeling

• Perform statistical analysis, exploratory data analysis, and predictive modeling on clinical and research datasets
• Apply machine learning and advanced analytics to healthcare data (e.g., outcomes prediction, risk modeling, disease phenotyping)
• Support hypothesis-driven research and investigator-initiated studies
• Collaborate with clinicians and investigators to translate research questions into analytical workflows

3. Clinical & Research Informatics

• Integrate data from Electronic Health Records (EHRs), laboratory systems, imaging systems, registries, and external datasets
• Support data extraction for clinical studies, audits, and publications
• Assist in development and maintenance of clinical dashboards, research databases, and reporting systems

4. Compliance, Ethics & Regulations

• Ensure compliance with institutional ethics committee (IEC/IRB) requirements, national regulations, and data protection laws
• Support regulatory inspections, audits, and reporting for funded and collaborative research projects
• Maintain documentation for data sharing agreements, funding agency requirements, and publications

5. Collaboration & Capacity Building

• Work closely with clinicians, biostatistician, research coordinators, and IT teams
• Train research staff on data entry standards, quality assurance, and basic analytics tools
• Support grant applications through data analysis plans and feasibility assessments

Required Qualifications

Education

• Master’s or PhD in Data Science, Biostatistics, Computer Science, Health Informatics, Epidemiology, Biomedical Engineering, or related field

Experience

• 3–7 years of experience in healthcare, clinical research, or academic research data environments
• Hands-on experience managing large, complex healthcare or research datasets

Technical Skills

• Proficiency in Python and/or R for data analysis
• Experience with SQL and relational databases
• Knowledge of statistical methods, machine learning, and predictive analytics
• Familiarity with clinical research data standards
• Experience with EHR data, clinical registries, or trial databases
• Data visualization tools (e.g., Tableau, Power BI, Python/R libraries)

Knowledge & Competencies

• Strong understanding of clinical research workflows and healthcare data
• Awareness of ethical, legal, and regulatory issues related to patient data
• Excellent analytical, problem-solving, and documentation skills
• Ability to communicate complex data insights to non-technical clinical stakeholders
• High attention to detail, data accuracy, and confidentiality