Company Description MedTourEasy Vizag is a growing organization focused on leveraging data to improve decision-making and operational efficiency in the healthcare and services ecosystem. The company values innovation, accuracy, and ethical data practices to support better outcomes for its partners and clients. Team members are encouraged to learn, experiment, and contribute ideas in a collaborative environment. MedTourEasy Vizag offers opportunities for skill development, mentorship, and exposure to modern data tools and methodologies.

Program Description The Data Analysis Trainee program at MedTourEasy Vizag is a full-time remote traineeship focused on learning and applying foundational data analysis skills. On a day-to-day basis, the trainee will assist with collecting, cleaning, and organizing data from various sources, and support basic data analysis tasks under the guidance of senior team members. The role includes preparing simple reports and visual summaries, helping to interpret trends, and documenting methods and findings in a clear and structured manner. The trainee will collaborate with colleagues across functions, participate in training sessions, and gradually take on more complex analytical tasks as skills develop.

Qualifications

Candidates should possess strong Analytical Skills and a foundational understanding of Data Analytics.
Candidates should possess knowledge of Statistics to support data interpretation and decision-making.
Candidates should possess effective Communication skills for explaining findings and collaborating with team members.
Candidates should possess basic Data Modeling skills or an interest in learning data modeling techniques.
Familiarity with spreadsheet tools (e.g., Excel, Google Sheets) and at least one data analysis or visualization tool (e.g., Python, R, Power BI, Tableau) is beneficial.
Ability to work independently in a remote environment, manage time effectively, and meet deadlines.
A degree or ongoing studies in a quantitative or related field (such as Data Science, Statistics, Computer Science, Engineering, Economics, or Mathematics) is preferred but not mandatory.
Curiosity, attention to detail, and a willingness to learn new tools and methodologies are highly valued.