Data Analysis Trainee

About the Role

MedTourEasy Dhanbad is a growing organization focused on using data and technology to improve access to healthcare and related services. The team works across locations and relies on digital tools to collaborate, analyze information, and support decision-making. As a developing company, MedTourEasy offers opportunities for trainees to work closely with mentors, learn practical skills, and contribute to real projects. The work culture values curiosity, responsibility, and the ability to learn quickly in a remote environment. The Data Analysis Traineeship is a remote program that supports data-driven decision-making across the organization.

Key Responsibilities

• Collect, clean, and organize data from different sources.
• Perform basic analyses.
• Assist in creating reports and dashboards.
• Interpret data trends.
• Prepare visualizations.
• Help team members understand key insights.
• Collaborate with colleagues via online tools.
• Document methods and findings clearly.
• Follow guidance from senior analysts to ensure accuracy and consistency.

Requirements & Tech Stack

• Excel or Google Sheets
• Exposure to SQL, Python, R, or data visualization tools (e.g., Power BI, Tableau) is an advantage.

Qualifications

• Strong Analytical Skills with the ability to interpret patterns, trends, and relationships in data.
• Basic to intermediate Data Analytics skills, including working with spreadsheets, databases, or analytics tools.
• Foundational knowledge of Statistics to understand measures like averages, distributions, correlations, and significance.
• Understanding of Data Modeling concepts, such as structuring data tables, relationships, and simple schemas.
• Effective Communication skills to explain findings clearly in writing and in discussions with non-technical stakeholders.
• Enrollment in or completion of a degree or certification in Data Science, Statistics, Computer Science, Economics, or a related field is preferred.
• Ability to work independently in a remote setting, manage time well, and maintain attention to detail.
• Willingness to learn, accept feedback, and adapt to new tools and methods in data analysis.