Data Analyst Trainee

About the Role

MedTourEasy is a healthcare technology organization focused on improving access to medical services and information through digital platforms. As a growing company, it offers opportunities for emerging professionals to gain hands-on experience in data-driven environments and contribute to meaningful healthcare initiatives. The Data Analytics Traineeship is a remote program designed for individuals seeking practical experience in data-driven decision-making within the healthcare technology domain.

Key Responsibilities

• Collecting, cleaning, and organizing data from various internal and external sources.
• Performing basic data analysis to identify trends, patterns, and key insights.
• Supporting data modeling activities under the guidance of senior team members.
• Assisting in preparing reports, dashboards, and visualizations to communicate findings clearly to stakeholders.
• Helping maintain data documentation and standards.
• Collaborating with cross-functional teams.
• Learning best practices in data management.
• Continuously developing analytical and technical skills throughout the traineeship.

Requirements & Tech Stack

• Familiarity with spreadsheets and analytical tools (e.g., Excel, SQL, Python, or R) is highly beneficial.

Qualifications

• Ability to apply Data Analytics and Data Analysis techniques to real-world business and healthcare problems.
• Strong Analytical Skills for interpreting datasets, identifying trends, and drawing logical conclusions.
• Foundational experience or coursework in Data Management, including data cleaning, organizing, and validation.
• Basic understanding of Data Modeling concepts and willingness to learn and support model development.
• Strong attention to detail and a problem-solving mindset.
• Ability to work independently in a remote setting.
• Effective written and verbal communication skills to present data findings clearly to non-technical audiences.
• Currently pursuing or recently completed a degree or certification in Data Science, Statistics, Computer Science, Engineering, or a related field.