Data Science & Machine Learning Intern

Job Description

Company: Zaalima Development Location: Remote Duration: 3 Months Stipend: 1,000 5,000/month (based on performance) Eligibility: Open to all students, freshers, and career switchers welcome About Zaalima Development: Zaalima Development is a forward-thinking tech company leveraging the power of data to build intelligent applications and systems. We believe in providing growth opportunities for aspiring professionals through real-world project experience and strong mentorship. Role Overview: We are seeking motivated Data Science & Machine Learning Interns to join our team. This internship is ideal for freshers who want to gain hands-on experience in building data pipelines, analyzing datasets, and developing machine learning models. Key Responsibilities: Work with structured and unstructured data for cleaning, preprocessing, and analysis Perform exploratory data analysis (EDA) to identify trends and patterns Build, evaluate, and improve machine learning models using Python libraries Contribute to real-world projects involving prediction, classification, or recommendation systems Document workflows, findings, and collaborate with cross-functional teams Requirements: Basic understanding of Python and data science fundamentals Familiarity with libraries such as pandas, NumPy, matplotlib, scikit-learn, or TensorFlow (preferred but not mandatory) Strong analytical and problem-solving skills Eagerness to learn and explore new tools and concepts No prior experience required What We Offer: Part-time remote internship with flexible working hours Stipend between 1,000 to 5,000 per month based on performance Real-world experience working on data-driven projects Mentorship from experienced data professionals Certificate of completion upon successful internship How to Apply: If you're enthusiastic about data, machine learning, and AI, and looking to kickstart your career with real project exposure, we encourage you to apply. This role is open to all learners who are ready to grow in a practical, hands-on environment.