Data Science Intern

Job Description

Data Science Intern 📍 Location: Remote (100% Virtual) 📅 Duration: 3 Months 💸 Stipend for Top Interns: ₹15,000 🎁 Perks: Certificate | Letter of Recommendation | Full-Time Offer (Based on Performance) About INLIGHN TECH INLIGHN TECH offers hands-on, project-based virtual internships that bridge the gap between academic knowledge and industry skills. Our Data Science Internship is curated to provide aspiring data professionals with real-world exposure in data collection, analysis, modeling, and decision-making using cutting-edge tools. 🚀 Internship Overview As a Data Science Intern , you’ll work on real-time datasets , apply machine learning models , and generate actionable insights . The role is ideal for individuals looking to strengthen their understanding of data pipelines, predictive modeling, and storytelling with data . 🔧 Key Responsibilities Clean, manipulate, and analyze structured and unstructured datasets Build and evaluate machine learning models for prediction/classification Apply statistical techniques to uncover trends and insights Work with tools such as Python, Pandas, NumPy, Scikit-learn, and Jupyter Notebooks Create visualizations using Matplotlib, Seaborn, or Power BI/Tableau Collaborate with mentors and peers to solve data-driven problems Document code, findings, and processes in clear and concise reports ✅ Qualifications Pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Engineering , or related fields Proficient in Python and familiar with Pandas, NumPy, and basic ML libraries Strong foundation in statistics, probability , and data visualization Understanding of supervised and unsupervised learning algorithms Eager to learn, experiment, and solve complex problems using data 🎓 What You’ll Gain Practical experience with real-world datasets and projects Exposure to machine learning workflows and tools Internship Certificate upon successful completion Letter of Recommendation for top performers Opportunity for a Full-Time Offer based on performance A portfolio of data science projects to showcase in interviews Show more Show less