Description

Day-to-Day Responsibilities

• Develop, maintain, troubleshoot, and optimize programs using R, Python, and SQL.
• Extract, clean, transform, merge, integrate, and validate data from multiple internal and external sources.
• Build and maintain research datasets and analytic files for healthcare, epidemiology, observational, and public health studies.
• Perform data programming and analysis to support research objectives and study requirements.
• Conduct data-quality assessments and validation checks to ensure accuracy, completeness, and consistency.
• Investigate data discrepancies and resolve issues through root-cause analysis
• Document programming methods, data sources, specifications, assumptions, processes, validation steps, and analytical results.
• Prepare reports, presentations, training materials, and technical documentation for project teams and stakeholders.
• Present programming activities, findings, data limitations, and quality-assurance results to research teams.
• Ensure the accuracy, quality, integrity, and reproducibility of research data and programming deliverables

Must-Have Qualifications

• Master’s degree in Biostatistics, Epidemiology, Public Health, Data Science, Statistics, Computer Science, Mathematics, or a closely related quantitative field.
• 0-2 years of experience in research programming, data analysis, research informatics, healthcare analytics, or a related field.
• Hands-on proficiency in R, Python, and SQL.
• Experience supporting healthcare, epidemiology, public health, biomedical, clinical, or observational research projects.
• Experience working with healthcare-related data, such as electronic health records, claims data, clinical data, population-health data, or research data warehouses

Key Skills

Education

Any Graduate