Title: Senior Data Scientist – GenAI, LLM & Advanced Analytics

Location: Thousand Lights, Chennai

Work Mode – Onsite (5 Days) Sat/Sun – Week Off

Department: Software Development

Positions: 1

Employment Type: Full Time

Remote: No

Notice Period: Upto 15 Days

About Colan Infotech - https://colaninfotech.com/

Colan Infotech is a fast-growing CMMI Level 3 digital transformation and technology services company delivering innovative solutions across AI, Cloud, Mobility, Web Applications, DevOps, and Product Engineering. With a strong global footprint spanning the US, UK, India, and GCC, we partner with organizations to build scalable, future-ready technology products.

Backed by a culture that values innovation, ownership, continuous learning, and collaboration, Colan Infotech provides an environment where people grow, contribute meaningfully, and make a real impact.

About the Role

We are seeking a highly skilled Senior Data Scientist with hands-on expertise in Machine Learning, Large Language Models (LLMs), and Generative AI. The role involves designing, building, and deploying production-grade AI systems, including agentic LLM workflows, forecasting engines, recommendation platforms, and fraud analytics solutions. The ideal candidate will collaborate with engineering and business stakeholders to translate requirements into scalable AI solutions and contribute to the organization's AI roadmap.

Key Responsibilities

GenAI & LLM Solutions

·        Develop LLM-powered applications using GPT, LLaMA, Mistral, Gemini, and transformer-based models

·        Build Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., Azure AI Search)

·        Develop multi-agent LLM systems using LangGraph (orchestrator, intent, guard, and domain agents)

·        Implement enterprise-grade prompt engineering and hierarchical prompting strategies

·        Ensure LLM output safety, quality, and guardrails for production deployment

Machine Learning & Analytics

·        Build ML models for forecasting, recommendation, fraud detection, churn prediction, and sentiment analytics

·        Apply advanced feature engineering, imbalanced data handling (SMOTE/ADASYN), and hyperparameter tuning

·        Perform statistical analysis including A/B testing, hypothesis testing, and model performance evaluation

NLP & Deep Learning

·        Implement NLP solutions using BERT, DistilBERT, Word2Vec, embeddings, and transformers

·        Perform topic modeling, sentiment analysis, and root cause analysis (RCA) on unstructured data

·        Build deep learning architectures (ANN, CNN, RNN, LSTM) using TensorFlow, PyTorch, and Keras

MLOps & Deployment

·        Manage end-to-end ML lifecycle using MLflow for experiment tracking and model registry

·        Develop CI/CD pipelines for training, validation, packaging, and deployment

·        Deploy ML and GenAI solutions using Azure Managed Online Endpoints

·        Ensure scalability, reliability, monitoring, and observability of deployed models

Cloud & Data Engineering

·        Work extensively on Microsoft Azure, with exposure to GCP and AWS

·        Build scalable APIs and services using Flask / Streamlit

·        Process and manage large datasets using SQL, PySpark, and cloud-native services

Required Skills & Experience

·        Experience: 8+ years in Data Science, ML, NLP, and Generative AI

·        Programming: Python, SQL (R is a plus)

·        ML Frameworks: scikit-learn, XGBoost, CatBoost, TensorFlow, PyTorch, FastAI

·        GenAI & LLMs: OpenAI, Hugging Face, LangChain, LangGraph, RAG pipelines

·        NLP: BERT, transformer-based models, embeddings, topic & sentiment modeling

·        MLOps: MLflow, CI/CD pipelines, model registry, deployment pipelines

·        Cloud: Azure (primary), GCP, AWS

·        Databases: SQL Server, MS Fabric, Vector Databases

What We Look For

·        Strong analytical and problem-solving skills

·        Proven experience deploying production-grade AI systems

·        Ability to bridge research-driven GenAI capabilities with enterprise use cases

·        Capability to work cross-functionally with engineering and product teams

·        Ability to operate in consulting, product, or fast-paced environments

·        Strong communication and stakeholder management skills

·        Leadership qualities including mentoring and code/model review

Preferred Qualifications

·        M.Tech / B.Tech in Computer Science, Data Science, AI, or related fields (IIT or equivalent preferred)

·        Certifications in LLMOps, GenAI, Deep Learning, or Statistical Modeling

·        Prior experience in developing enterprise-grade agentic LLM systems