Field Data Analyst

Company Description MUS Global Services Pvt. Ltd. is a growing services organization focused on delivering data-driven solutions and operational support to clients across diverse sectors. The company emphasizes practical, field-based insights to help organizations improve decision-making and efficiency. Team members collaborate closely with stakeholders to collect, analyze, and interpret data that informs real-world outcomes. MUS Global Services values integrity, accuracy, and continuous learning, offering opportunities for emerging professionals to develop strong analytical and technical skills.

Role Description The Field Data Analyst internship role is an on-site position based in Bihar. The intern will collect data from field locations, verify its accuracy, and input information into structured formats and databases. Daily responsibilities include supporting data cleaning and basic analysis, preparing simple reports or summaries, and assisting with data visualization for internal teams. The role involves coordinating with local stakeholders, documenting observations, and reporting any inconsistencies in field data. Interns are expected to follow established data collection protocols, maintain confidentiality, and contribute to improving data quality and reporting processes.

Qualifications

• Candidates should possess strong Analytical Skills and a solid understanding of Data Analytics.
• Candidates should possess foundational knowledge of Statistics and familiarity with Data Modeling concepts.
• Candidates should possess clear and effective Communication skills for interacting with field teams and stakeholders.
• Relevant skills such as proficiency in spreadsheets or basic data tools (e.g., Excel), attention to detail, and problem-solving abilities are beneficial.
• Enrollment in or completion of a degree in statistics, mathematics, economics, engineering, data science, or a related field is preferred.
• Ability to work on-site in Bihar, follow field procedures, and adapt to changing conditions in the field environment is required.