Data Scientist Internship

Job Description

Job Description : Requirements: Currently pursuing a degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. Technical Skills: Programming Languages: Proficiency in Python. Machine Learning: Basic understanding of machine learning concepts and algorithms (supervised and unsupervised learning). Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Data Handling and Processing: Proficiency in data manipulation and analysis using pandas and numpy. Familiarity with data cleaning, preprocessing, and transformation techniques. Statistical Analysis: Understanding of basic statistical concepts and methods. Experience with statistical modeling and hypothesis testing. Databases: MySQL. Data Visualization: Experience with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly). Natural Language Processing (NLP): Basic understanding of NLP concepts and techniques. Familiarity with NLP libraries such as NLTK, SpaCy, or Hugging Face Transformers Computer Vision: Basic understanding of computer vision techniques. Experience with image processing libraries such as OpenCV. LLM: .Basic knowledge of using different LLMS and how to prompting. Web Development: Familiarity with web frameworks such as Django or Flask Cloud: Basic understanding at least one cloud like GCP,AWS, AND AZURE. Assist in building scalable AI/ML solutions across various domains such as NLP, Computer Vision, Clustering, Segmentation, and Deep Learning. Collaborate with senior team members to understand business problems and identify suitable data-driven techniques for solving them. Help in prototyping solutions and building models to test the feasibility of different approaches. Participate in the development, training, and testing of statistical models to achieve optimal performance. Contribute to the creation and maintenance of robust, scalable, and production-grade data pipelines and machine learning models. Write reusable code following best software engineering practices and design patterns. Support the team in reporting and data visualization tasks, applying statistical modeling and supervised learning tools where appropriate. Work in a collaborative team environment, striving to build quality systems that provide business value. Communicate effectively with team members and stakeholders to understand requirements and deliverables.