Data Science Intern

Required Qualifications:

• Currently pursuing or recently graduated from a premium institute , expected to graduate in 2025 (e.g., IITs, NITs, ISBs, BITS, or similar).
• Solid understanding of machine learning models and Natural Language Processing techniques, including supervised and unsupervised learning, text classification and language models.
• Strong proficiency in Python , with experience in libraries such as Pandas , NumPy , Scikit-learn , TensorFlow/ PyTorch for data processing and machine learning.
• Proficiency in SQL , with the ability to write and optimize complex queries for analyzing large datasets.
• Strong understanding of A/B testing , hypothesis testing , and statistical evaluation techniques.
• Excellent analytical and problem-solving skills , with the ability to work on large-scale data problems and derive actionable insights.
• Strong communication skills to present technical findings to non-technical stakeholders and team members.
• Good to Have: Understanding of AWS Cloud Services (S3, EC2, Redshift) for deploying models and working with cloud infrastructure.

• Build end-to-end machine learning models from scratch, starting with data fetching and preprocessing, followed by feature engineering, model training, evaluation to solve business problems and drive impactful outcomes.
• Data Analysis with Amazon Redshift : Use Amazon Redshift to query large datasets, perform exploratory data analysis, and build data pipelines for processing structured and unstructured data.
• Model Deployment : Deploy machine learning models using AWS Cloud services (e.g. EC2, Lambda, S3), serving them either as APIs or batch processes.
• Conduct A/B testing experiments to evaluate model performance, analyze the results, and assess the impact of models on key business metrics.
• Collaboration: Work closely with cross-functional teams, including other data scientists, data analysts, engineers to implement data-driven solutions.
• Reporting & Visualization: Develop dashboards, visualizations, and reports to communicate findings, insights, and model results effectively to stakeholders.