Data Scientist - L3

Key Responsibilities

• Collaborate with business stakeholders to translate problem statements into data science tasks.
• Perform data collection, cleaning, feature engineering, and exploratory data analysis (EDA).
• Build and evaluate ML models using Python and libraries such as scikit-learn and XGBoost.
• Support the development of LLM-powered workflows like RAG (Retrieval-Augmented Generation), prompt engineering, and fine-tuning for use cases including summarization, Q&A, and task automation.
• Contribute to GenAI application development using frameworks like LangChain, OpenAI APIs, or similar ecosystems.
• Work with engineers to integrate models into applications, build/test APIs, and monitor performance post-deployment.
• Maintain reproducible notebooks, pipelines, and documentation for ML and LLM experiments.
• Stay updated on advancements in ML, NLP, and GenAI, and share insights with the team.
  

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• 6–9 years of experience in data science, ML, or AI (projects and internships included).
• Proficiency in Python with experience in libraries like pandas, NumPy, scikit-learn, and matplotlib.
• Basic exposure to LLMs (e.g., OpenAI, Cohere, Mistral, Hugging Face) or a strong interest with the ability to learn quickly.
• Familiarity with SQL and structured data handling.
• Understanding of NLP fundamentals and vector-based retrieval techniques (a plus).
• Strong communication, problem-solving skills, and a proactive attitude.
  

Nice-to-Have (Not Mandatory)

• Experience with GenAI prototyping using LangChain, LlamaIndex, or similar frameworks.
• Knowledge of REST APIs and model integration into backend systems.
• Familiarity with cloud platforms (AWS/GCP/Azure), Docker, or Git.