Data Manager

Job Group KMR 5. PRIME-KS Study (Precision Imaging to Evaluate Kaposi Sarcoma), KEMRI in collaboration with Washington University in St. Louis, funded by NIH/NCI.

Duties and responsibilities

• Design, develop, test, and maintain electronic data collection tools, CRFs, and databases using ODK, REDCap, Epi Info, Excel and other platforms.
• Implement study protocols, SOPs, and Data Management Plans.
• Coordinate data collection, entry, cleaning, validation, and discrepancy resolution.
• Develop Statistical Analysis Plans aligned with study objectives, protocols and regulatory requirements.
• Analyse complex datasets, including longitudinal, cohort, and multilevel data, using appropriate statistical methods.
• Ensure data security, confidentiality, backup, and controlled access in compliance with the Data Protection Act and institutional policies.
• Develop dashboards, statistical summaries, and visual reports using Power BI, Tableau, Excel and other tools.
• Prepare data management and statistical documentation, conduct database quality checks, and ensure data readiness for analysis and regulatory submissions.
• Prepare and submit timely data monitoring and progress reports to the study team, sponsors, and DSMB.
• Contribute to research abstracts, manuscripts, and other scientific outputs.

Minimum qualifications

• Bachelor's Degree in Statistics or Biostatistics
• Master's degree in Statistics, Biostatistics, Epidemiology, or a related field
• Minimum three years working experience
• Proficiency in at least one software package (e.g. SAS/STATA/R/SPSS) for analysis and data cleaning for a minimum of three years
• Demonstrable oral & written communication skills / fluency in English

Key skills and competences

• Experience managing and analysing large datasets, particularly from repeated cross-sectional surveys and longitudinal studies
• Strong organisational and time-management skills; ability to work independently
• Good knowledge of public health, epidemiological principles, and disease surveillance methods
• Strong analytical, problem-solving, and data interpretation skills
• Proficiency in statistical analysis software and data management tools
• High standards of accuracy, data integrity, confidentiality, and adherence to research protocols
• Strong written and verbal communication skills, including presenting statistical findings clearly