Data Analysis Trainee

Company Description MedTourEasy is an emerging organization focused on leveraging data to improve healthcare and related services. The company values innovation, analytical thinking, and technology-driven solutions to support better decision-making. Team members collaborate in a flexible environment that encourages continuous learning and professional growth. MedTourEasy offers opportunities to work on impactful projects that contribute to meaningful outcomes for clients and stakeholders.

Role Description The Data Analysis Trainee role at MedTourEasy is a full-time remote position focused on learning and supporting data-driven decision-making. Day-to-day responsibilities include collecting, cleaning, and organizing data sets, performing basic statistical analyses, and assisting in building simple data models under guidance from senior team members. The trainee will help prepare reports, visualizations, and summaries that communicate key findings to internal teams and stakeholders. The role also involves documenting analysis processes, collaborating with mentors and colleagues, and proactively developing skills in data analytics tools and methods. This position is designed for individuals who are eager to grow into a data analytics professional through hands-on experience and structured training.

Qualifications

• Candidates should possess strong Analytical Skills and foundational Data Analytics capabilities.
• Candidates should possess basic knowledge of Statistics and experience applying statistical concepts to datasets.
• Candidates should possess introductory skills in Data Modeling and an understanding of data structures or databases.
• Candidates should possess clear and effective Communication skills for presenting findings and collaborating with teams.
• Candidates should ideally be familiar with tools such as Excel, SQL, or introductory data analysis software (e.g., Python, R).
• Candidates should demonstrate attention to detail, a willingness to learn, and the ability to work independently in a remote environment.
• A bachelor's degree or ongoing studies in a quantitative field such as Data Science, Statistics, Computer Science, Engineering, or a related discipline is preferred.