Senior Analyst - Data Science (R-19578)

Key Responsibilities:

Support and contribute to Generative AI initiatives across the organization.

Develop and deploy GenAI applications using LLMs and AI frameworks.

Leverage models such as GPT, Gemini, and LLaMA for AI-powered solutions.

Build and manage multi-agent AI systems.

Develop solutions using LangChain, LangGraph, FastAPI, Streamlit, Chainlit, and Transformers.

Integrate AI capabilities into enterprise applications through APIs and cloud-native architectures.

Design and implement RAG pipelines using vector databases such as FAISS, Qdrant, Weaviate, and ChromaDB.

Collaborate with stakeholders to understand requirements and deliver AI-driven business solutions.

Provide analysis, insights, and recommendations to support business needs.

Stay current with emerging Generative AI technologies, tools, and best practices.

Key Requirements:

Bachelor's degree in computer science, Engineering, Statistics, or a related technical field

6 - 8 years of experience in Data Analytics, Data Science, or Generative AI roles.

Strong experience delivering data-driven and AI solutions in production environments.

Proficiency in Python, PySpark, and SQL.

Hands-on experience with data science libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib.

Experience with GenAI platforms and tools, including OpenAI, Anthropic, Google Vertex AI, FastAPI, Gradio, and Streamlit.

Strong understanding of RAG (Retrieval-Augmented Generation) and Agentic AI architectures using LangChain and Lang Graph.

Experience developing and deploying APIs using Fast API or similar frameworks.

Knowledge of MLOps practices and machine learning deployment workflows is a plus.

Strong analytical, problem-solving, communication, and stakeholder management skills.