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Data Analyst

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About the Role:


As a Data Analyst , you will assist the Analytics and Business Intelligence team in collecting, cleaning, analyzing, and interpreting data to support strategic decision-making. This internship will help you understand end-to-end data analysis processes, enhance your analytical and technical skills, and gain practical experience working with real-world business data.

Key Responsibilities:


  • Assist in collecting, cleaning, and organizing data from various internal and external sources.

  • Analyze large datasets to identify trends, patterns, and insights that drive business decisions.

  • Create and maintain dashboards and reports to track key performance indicators (KPIs).

  • Support the team in preparing data visualizations and presentations for stakeholders.

  • Collaborate with cross-functional teams to understand business requirements and translate them into data-driven insights.

  • Ensure data accuracy, consistency, and integrity across all reporting systems.

  • Assist in automating data collection and reporting processes.

  • Contribute to the improvement of data management and analysis workflows.

Qualifications & Skills:


  • Currently pursuing or recently completed a Bachelor’s or Master’s degree (preferably in Data Science, Statistics, Computer Science, Economics, Mathematics, or a related field).

  • Strong analytical and problem-solving skills .

  • Proficiency in MS Excel and basic understanding of data visualization tools (e.g., Power BI, Tableau).

  • Familiarity with SQL , Python , or R for data manipulation and analysis is a plus.

  • Attention to detail and ability to work with large datasets.

  • Strong communication skills and ability to present findings clearly.

  • Eagerness to learn and adapt in a fast-paced environment.

What You’ll Learn:


  • End-to-end data analysis lifecycle — from data collection to visualization.

  • Data cleaning, transformation, and validation techniques.

  • Use of modern analytics tools and technologies (Excel, Power BI, SQL, etc.).

  • How to translate data insights into business recommendations.

  • Real-world data analytics and reporting best practices.



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