Data Analysis Trainee

Company Description MedTourEasy AP is a global healthcare company that provides individuals and organizations with information to evaluate international healthcare options. The company delivers analytical solutions to partner healthcare providers around the world, helping them make data-driven decisions and improve patient services. MedTourEasy AP focuses on using data and analytics to enhance transparency, efficiency, and quality in global healthcare. Team members have the opportunity to contribute to projects that support international healthcare access and innovation.

Program Description This remote traineeship program in Data Analysis involves supporting data-driven initiatives for MedTourEasy AP's global healthcare partners. Day-to-day tasks include collecting, cleaning, and organizing healthcare-related datasets, conducting basic statistical analysis, and assisting with data modeling to identify trends and insights. The intern will help prepare reports, visualizations, and summaries that communicate findings to internal stakeholders and external partners. The role also includes collaborating with cross-functional teams, documenting analytical processes, and learning best practices in healthcare data analytics. This is a structured internship position designed to build practical experience in data analysis within the healthcare sector.

Qualifications

• Candidates should possess strong Analytical Skills and foundational Data Analytics capabilities.
• Candidates should possess a working knowledge of Statistics and experience with Data Modeling concepts.
• Candidates should possess clear and professional Communication skills for presenting data insights.
• Candidates should possess familiarity with spreadsheet tools and basic data visualization (e.g., Excel, Google Sheets, Tableau or similar).
• Candidates should possess an ability to work independently in a remote setting, manage time effectively, and collaborate in virtual teams.
• Enrollment in or completion of a degree program in Data Science, Statistics, Computer Science, Public Health, or a related field is beneficial.
• Interest in healthcare analytics, global health, or health technology and willingness to learn new tools and methodologies is preferred.