Data Science & Analytics Intern

As a member of the data science team, you will have the opportunity to work on cutting-edge analytics technologies, develop predictive models, and contribute to data-driven decision making. The role focuses on end-to-end data science workflows, advanced statistical analysis, and real-world AI applications in business contexts. Key Responsibilities: - Conduct comprehensive data collection, cleaning, preprocessing, and exploratory data analysis using Python, R, and SQL frameworks. - Develop and implement machine learning models for classification, regression, clustering, and time-series forecasting applications. - Create advanced data visualizations and interactive dashboards using Tableau, Power BI, matplotlib, and seaborn libraries. - Perform statistical analysis, hypothesis testing, and A/B testing to derive actionable business insights. - Build and deploy predictive analytics models to support business strategy and operational optimization. - Collaborate with cross-functional teams to translate business requirements into analytical solutions and recommendations. - Document analytical processes, create technical reports, and present findings to stakeholders through compelling data storytelling. Qualifications Required: Must-Haves: - Bachelors or Masters degree in Data Science, Statistics, Computer Science, Mathematics, or related field (final year students or recent graduates). - Strong programming proficiency in Python with experience in NumPy, Pandas, Scikit-learn, and Jupyter Notebooks. - Solid understanding of statistical concepts including descriptive statistics, probability distributions, and inferential statistics. - Knowledge of SQL for database querying and data manipulation from various data sources. - Experience with data visualization tools and techniques for creating meaningful insights from complex datasets. Nice-to-Haves: - Hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or advanced scikit-learn applications. - Familiarity with cloud platforms (AWS, GCP, Azure) for data processing, model deployment, and distributed computing. - Knowledge of big data technologies including Spark, Hadoop, or NoSQL databases for large-scale data processing. - Experience with advanced analytics techniques including deep learning, NLP, or computer vision applications. - Previous internship experience or portfolio projects demonstrating real-world data science problem-solving capabilities.,