Junior Data Scientist

Role Overview: As a Data Scientist, your main responsibility will be to manipulate and preprocess structured and unstructured data to prepare datasets for analysis and model training. You will utilize Python libraries such as PyTorch, Pandas, and NumPy for data analysis, model development, and implementation. Additionally, you will fine-tune large language models (LLMs) to meet specific use cases and enterprise requirements. Collaboration with cross-functional teams to experiment with AI/ML models and iterate quickly on prototypes will also be a key part of your role. You will optimize workflows to ensure fast experimentation and deployment of models to production environments. Implementing containerization and basic Docker workflows to streamline deployment processes will also be part of your responsibilities. Writing clean, efficient, and production-ready Python code for scalable AI solutions will be essential. Key Responsibilities: - Manipulate and preprocess structured and unstructured data for analysis and model training. - Utilize Python libraries like PyTorch, Pandas, and NumPy for data analysis and model development. - Fine-tune large language models to meet enterprise requirements. - Collaborate with cross-functional teams to experiment with AI/ML models. - Optimize workflows for fast experimentation and deployment of models. - Implement containerization and basic Docker workflows for deployment processes. - Write clean, efficient, and production-ready Python code for scalable AI solutions. Qualifications Required: - Proficiency in Python with strong skills in libraries like PyTorch, Pandas, and NumPy. - Experience in handling both structured and unstructured datasets. - Familiarity with fine-tuning LLMs and understanding modern NLP techniques. - Basics of Docker and containerization principles. - Demonstrated ability to experiment, iterate, and deploy code rapidly in a production setting. - Strong problem-solving mindset with attention to detail. - Ability to learn and adapt quickly in a fast-paced, dynamic environment. (Note: No additional details about the company were provided in the job description),