Senior Data Scientist

Jobtailor; Chennai District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Jobtailor in Chennai, Tamil Nadu, India is seeking a senior GenAI/Data Analytics professional to lead development and deployment of AI solutions. You will drive Generative AI initiatives across the organization, leveraging LLMs and AI frameworks to build scalable applications.

Ideal candidates bring 6–8 years in data analytics or AI roles, proficiency in Python, PySpark, SQL, and hands-on experience with Pandas, NumPy, and ML libraries.

Qualifications

• 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 and Agentic AI architectures using LangChain and Lang Graph.
• Experience developing and deploying APIs using FastAPI or similar frameworks.
• Knowledge of MLOps practices and ML deployment workflows is a plus.
• Strong analytical, problem-solving, communication, and stakeholder management skills.

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.

Skills

Analytical thinking

Communication

Stakeholder management

Education

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

Tools

Python

PySpark

SQL

Pandas

NumPy

Scikit-learn

Matplotlib

FastAPI

Gradio

Streamlit

LangChain

LangGraph

FAISS

Qdrant

Weaviate

ChromaDB

OpenAI

Anthropic

Vertex AI

Job description

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.

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.