Data Analyst Intern

Job Description

📊 Data Analyst Intern 📍 Location: Remote (100% Virtual) 📅 Duration: 3 Months 💸 Stipend for Top Interns: ₹15,000 🎁 Perks: Certificate | Letter of Recommendation | Full-Time Offer (Performance-Based) About INLIGHN TECH INLIGHN TECH is a forward-thinking edtech company that provides hands-on, project-based virtual internships. The Data Analyst Internship is designed for students and recent graduates eager to gain real-world experience in analyzing data, extracting insights, and supporting data-driven decisions. 🚀 Internship Overview As a Data Analyst Intern , you will work with real datasets to perform analysis, build dashboards, and communicate insights that help solve business challenges. You'll learn to interpret data trends and use analytical tools to support strategic decisions. 🔧 Key Responsibilities Collect, clean, and analyze data from various sources Perform exploratory data analysis (EDA) to identify patterns and trends Build visual dashboards using Power BI , Tableau , or Google Data Studio Write and optimize SQL queries for data extraction and manipulation Use Excel , Python (Pandas, NumPy) for data processing Present findings through reports, visualizations, and presentations Collaborate with cross-functional teams to support data initiatives ✅ Qualifications Pursuing or recently completed a degree in Data Analytics, Statistics, Computer Science, Business, or related fields Proficiency in Excel and basic knowledge of SQL and Python Familiarity with data visualization tools such as Power BI or Tableau Strong analytical, problem-solving, and communication skills Ability to work independently and manage time effectively Passion for data and interest in solving real-world problems 🎓 What You’ll Gain Hands-on experience with real-world data and tools A professional portfolio of data projects and visual reports Internship Certificate upon completion Letter of Recommendation for top performers Opportunity for a Full-Time Role based on performance Exposure to industry-standard practices in data analysis and business intelligence