Data Analyst Training

Company Description MedTourEasy is an AI-powered healthcare analytics platform that provides deep insights across clinical, operational, and financial data. The organization supports healthcare providers with real-time analytics, predictive models, and intelligent dashboards to improve patient outcomes and resource utilization. MedTourEasy focuses on enabling data-driven decisions that enhance operational performance and care quality. Through its Medlytics solutions, the company empowers healthcare teams to make smarter, timely decisions based on reliable data.

Programme Description This is a remote traineeship role for a Data Analyst at MedTourEasy. The Data Analyst Trainee will work with healthcare datasets to clean, transform, and validate data for reporting and analysis. Responsibilities include building and maintaining dashboards, generating summary reports, and supporting the development of predictive and statistical models. The programme involves collaborating with cross-functional teams to understand data needs, presenting findings in a clear and structured manner, and documenting methodologies and results. The trainee will also support ad-hoc analyses to answer specific business and clinical questions and help improve data quality and workflows.

Qualifications

• Candidates should possess strong Analytical Skills and Data Analytics capabilities.
• Candidates should possess knowledge of Statistics and experience applying statistical methods to real-world data.
• Candidates should possess Data Modeling skills, including structuring datasets and designing data schemas or models.
• Candidates should possess clear Communication skills for explaining insights to technical and non-technical stakeholders.
• Familiarity with tools such as Excel, SQL, Python or R, and data visualization platforms (e.g., Power BI, Tableau) is beneficial.
• Enrollment in or completion of a degree program in Data Science, Statistics, Computer Science, Engineering, Healthcare Informatics, or a related field is preferred.
• Attention to detail, ability to work independently in a remote setting, and interest in healthcare analytics are important.