Senior Data Scientist

Generative AI & LLMs

Fine-tune and apply large language models (LLMs) for summarization, classification, generation, and dialogue use cases.

Design and implement retrieval-augmented generation (RAG) pipelines using vector databases.

Develop intelligent agents, agentic workflows and chat-based interfaces that translate natural language into actions or insights.

Build multi-agent orchestration frameworks using tools such as LangGraph , AutoGen , or similar for enterprise-grade use cases.

Create reusable prompt templates and evaluation strategies to ensure output quality and relevance.

Machine Learning & Predictive Analytics

Develop robust ML models for classification, regression, clustering, and time-series forecasting.

Apply advanced feature engineering, model evaluation, and explainability techniques.

Collaborate with stakeholders to define data-driven solutions aligned with business KPIs.

Deployment& MLOps

• Lead the full model lifecycle from experimentation to deployment preferably using Azure , Databricks , or equivalent platforms.
  
• Monitor model performance, automate retraining, and ensure reliability through MLOps best practices.
  
  Data Strategy & Collaboration
  

  • Work with data engineers to transform raw data into ML-ready datasets.
    
  • Collaborate cross-functionally with product managers, developers, and business teams to turn use cases into scalable AI solutions.
    
  • Mentor junior team members and contribute to AI/ML best practices across the org.