Data Science Intern (Paid Internship)
Company: Infrabyte Consulting
Location: Remote
Duration: 1–3 Months
Stipend: ₹15,000 per month
Job Type: Internship (Full-Time)
Opportunity: Certificate of Internship + Full-Time Role Based on Performance
About Infrabyte Consulting
Infrabyte Consulting is an IT and analytics-focused company delivering innovative solutions in data science, machine learning, automation, and business intelligence. Our internship programs are designed to offer real-world analytical and modeling experience for aspiring data professionals.
Role Overview
We are looking for an enthusiastic Data Science Intern to join our data and AI team. This internship provides hands-on experience in data preprocessing, visualization, and building machine learning models using real datasets.
Key Responsibilities
• Collect, clean, and preprocess structured and unstructured data.
• Perform Exploratory Data Analysis (EDA) to identify patterns and insights.
• Build and evaluate machine learning models using techniques such as regression, classification, clustering, and time series analysis.
• Use Python libraries like Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn.
• Assist in developing predictive analytics solutions for internal and client projects.
• Create visualizations and reports to communicate findings clearly.
• Document workflows, experiments, and results.
Requirements
• Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Mathematics, or related fields.
• Strong understanding of Python, statistics, and machine learning fundamentals.
• Familiarity with ML libraries (Scikit-learn, TensorFlow, Keras) is an added advantage.
• Basic knowledge of SQL for data extraction is preferred.
• Good analytical thinking, problem-solving skills, and attention to detail.
• Passion for learning and applying data science concepts in real-world scenarios.
Perks & Benefits
• Stipend of ₹15,000 per month.
• Internship certificate after completion.
• Mentorship from experienced data scientists and ML engineers.
• Exposure to real-world projects and industry tools.
• Opportunity for a full-time position based on performance.