Data Scientist || 3rd Party Contract

This is a 3rd party contractual role. Location is Kolkata.

If you have relevant experience and comfortable with 3rd party contractual role then only apply.

Job Description – Data Scientist (Machine Learning & Generative AI)

Position Summary

We are looking for a Data Scientist / AI-ML Engineer with hands-on experience in Machine Learning, Generative AI, LLMs, RAG and Agentic AI. The role involves building and deploying production-grade AI applications using Python, LangChain/LangGraph, Vector Databases and REST APIs.

Key Responsibilities

Machine Learning Development

• Design, develop, evaluate, and deploy Machine Learning models for classification, regression, forecasting, clustering, recommendation systems, anomaly detection, and optimization problems.
• Perform exploratory data analysis (EDA), feature engineering, feature selection, and model tuning.
• Develop robust data preprocessing and feature engineering pipelines.
• Build reusable ML components and production-ready prediction services.
• Monitor model performance and implement continuous improvements and retraining strategies.
• Develop explainable and interpretable ML solutions wherever applicable.

Generative AI Development

• Design and develop Generative AI applications using Large Language Models (LLMs).
• Build Retrieval Augmented Generation (RAG) systems using Vector Databases.
• Develop intelligent AI assistants, copilots, chatbots, document intelligence, knowledge search, and workflow automation solutions.
• Implement prompt engineering strategies for reliable and accurate AI responses.
• Develop Agentic AI workflows using orchestration frameworks.
• Build document ingestion, indexing, embedding, retrieval, and semantic search pipelines.
• Optimize LLM performance, latency, token utilization, and response quality.

AI Application Development

• Develop scalable backend services for ML and GenAI applications.
• Build REST APIs for AI models and services.
• Deploy AI applications using containerized environments.
• Design modular and reusable AI application architectures.
• Integrate AI models with enterprise applications and business workflows.
• Develop logging, monitoring, exception handling, and performance optimization mechanisms.

Model Deployment & MLOps

• Package and deploy ML/AI models into production.
• Build automated inference pipelines.
• Monitor model drift, data drift, and application performance.
• Maintain model versioning and deployment pipelines.
• Troubleshoot production issues and optimize system reliability.

Data Engineering & Database Management

• Develop SQL queries and data extraction pipelines.
• Work with structured and semi-structured datasets.
• Design efficient database interactions for AI applications.
• Build data pipelines supporting AI model training and inference.

Research & Innovation

• Stay current with advancements in Machine Learning, Deep Learning, Generative AI, LLMs, Agentic AI, and AI infrastructure.
• Evaluate emerging AI frameworks, tools, and libraries.
• Recommend and prototype innovative AI solutions for business problems.

Required Technical Skills

Programming

• Python (Advanced)
• Object-Oriented Programming
• Python Packaging and Virtual Environments
• Git Version Control

Machine Learning

Strong hands-on experience with

• Scikit-learn
• Statsmodels
• NumPy
• Pandas
• Model Evaluation Techniques
• Hyperparameter Tuning
• Feature Engineering
• Time Series Analysis
• Classification
• Regression
• Clustering
• Forecasting
• Ensemble Learning

Generative AI

Experience with

• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval Augmented Generation (RAG)
• Embeddings
• Semantic Search
• Document Processing
• AI Agents
• Multi-Agent Workflows
• Context Management
• Function Calling / Tool Use
• Structured Output Generation

AI Frameworks

Hands-on experience with one or more

• LangChain
• LangGraph(preferred)
• LlamaIndex
• Hugging Face ecosystem (preferred)

Vector Databases

Experience with one or more

• FAISS
• Chroma
• Qdrant

Databases

• PostgreSQL
• SQL
• Database Design
• Query Optimization

API Development

Experience developing REST APIs using

• FastAPI
• Flask

Knowledge of

• JSON
• REST Principles
• Authentication
• API Documentation
• Async Programming (preferred)

Deployment & DevOps

Experience with

• Docker
• Containerized Deployments
• Linux Environment
• Basic CI/CD Concepts
• Environment Management
• Application Monitoring

Preferred Skills

Exposure to one or more of the following would be advantageous

• Deep Learning frameworks such as TensorFlow or PyTorch
• Computer Vision
• Natural Language Processing
• OCR and Document AI solutions
• Cloud platforms (AWS, Azure, or Google Cloud)
• MLflow or similar model management tools
• Kubernetes( Optional)
• Message Queues
• Vector Search Optimization
• AI Security and Responsible AI practices

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Artificial Intelligence, Mathematics, Engineering, or a related discipline.

Experience

• 2–6 years of hands-on experience in Machine Learning, Data Science, or AI application development.
• Experience developing production-grade AI solutions is preferred.
• Demonstrated experience in deploying and maintaining ML or Generative AI applications.

Desired Competencies

• Strong analytical and problem-solving skills.
• Ability to translate business requirements into AI solutions.
• Excellent debugging and troubleshooting abilities.
• Strong software engineering practices and coding standards.
• Good communication and documentation skills.
• Ability to work independently and collaboratively within cross-functional teams.
• Continuous learning mindset and passion for emerging AI technologies.

What Success Looks Like

The successful candidate will be able to

• Develop scalable Machine Learning and Generative AI solutions.
• Deliver production-ready AI applications with high reliability.
• Build reusable AI components and APIs.
• Continuously improve AI model accuracy and application performance.
• Contribute to the organization's AI innovation initiatives while maintaining high engineering standards.