Data Scientist

Job Summary: We are seeking an experienced and highly motivated Senior Data Scientist with a strong background in Generative AI , agentic systems , and end-to-end deployment of AI solutions. This role demands proficiency not only in building intelligent systems but also in operationalizing them using MLOps best practices and cloud-based deployment strategies. The ideal candidate will thrive at the intersection of data science, software engineering, and infrastructure. Key Responsibilities: Design, develop, and deploy advanced AI-powered chatbots and agent-based solutions using frameworks like LangChain and LangGraph . Build and maintain backend APIs and user-facing interfaces using FastAPI and Streamlit . Leverage Snowflake for data integration, transformation, and analytics. Implement and manage MLOps pipelines for model training, validation, versioning, and monitoring. Deploy models and applications on AWS and GCP , ensuring scalability, reliability, and security. Use Redis for caching and real-time data access in production-grade applications. Collaborate with cross-functional teams to translate business needs into technical solutions. Prepare and deliver effective presentations to stakeholders and leadership teams. Ensure code quality, testing, and documentation in Python environments. Required Skills: 5–8 years of hands-on experience in Data Science , with a focus on deployment. Proven experience in Chatbot development , Agentic AI , and LLM-based frameworks . Strong Python programming skills, including use of PyTorch , LangChain , and LangGraph . Proficient in MLOps practices : CI/CD for ML, model monitoring, version control, and automated retraining. Experience deploying solutions on cloud platforms (AWS, GCP). Backend and app development experience with FastAPI , Streamlit , and Redis . Strong working knowledge of Snowflake and data engineering workflows. Excellent communication and presentation skills , with the ability to convey technical topics to non-technical audiences. Experience with containerization tools like Docker and orchestration with Kubernetes . Exposure to prompt engineering and LLM fine-tuning. Nice to Have: Familiarity with tools like MLflow , DVC , Vertex AI . Experience working in agile product teams or startup environments. Show more Show less