Junior Data Scientist

Responsibilities :

1. Manipulate and preprocess structured and unstructured data to prepare datasets for analysis and model training.
2. Utilize Python libraries like PyTorch, Pandas, and NumPy for data analysis, model development, and implementation.
3. Fine-tune large language models (LLMs) to meet specific use cases and enterprise requirements.
4. Collaborate with cross-functional teams to experiment with AI/ML models and iterate quickly on prototypes.
5. Optimize workflows to ensure fast experimentation and deployment of models to production environments.
6. Implement containerization and basic Docker workflows to streamline deployment processes.
7. Write clean, efficient, and production-ready Python code for scalable AI solutions.

Good to Have:

• Exposure to cloud platforms like AWS, Azure, or GCP.
• Knowledge of MLOps principles and tools.
• Basic understanding of enterprise Knowledge Management Systems.
• Ability to work against tight deadlines.
• Ability to work on unstructured projects independently.
• Strong initiative and self-motivated
• Strong Communication & Collaboration acumen.

• Required Skills:
  • 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 of 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.