Data Scientist

Job Description

Req ID: 328578 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Data Scientist to join our team in Bangalore, Karn taka (IN-KA), India (IN). Job Title: Data Scientist Location: Bangalore (Hybrid) Experience: 5-7 years Job Summary: We are looking for a versatile and innovative Data Scientist with experience in Azure Cloud , .NET , ReactJS , and Python (LangChain & FastAPI) to join our cross-functional team. This role blends data science expertise with full-stack development and cloud deployment, enabling intelligent solutions that scale. Key Responsibilities: Design and implement machine learning models and NLP pipelines using Python, LangChain, and FastAPI. Develop and deploy data-driven applications on Microsoft Azure , leveraging services like Azure ML, Azure Functions, and Azure Data Lake. Collaborate with backend developers using .NET and frontend developers using ReactJS to integrate AI models into scalable web applications. Build APIs and microservices to serve ML models and data insights. Perform data wrangling, feature engineering, and model evaluation. Create dashboards and visualizations to communicate insights to stakeholders. Ensure security, scalability, and performance of deployed solutions in the Azure environment. Required Skills & Qualifications: Bachelor s or Master s degree in Computer Science, Data Science, or a related field. Strong experience with Python , especially LangChain , FastAPI , and data science libraries (pandas, scikit-learn, etc.). Proficiency in .NET (C#) for backend development. Experience with ReactJS for building interactive UIs. Hands-on experience with Azure Cloud Services (e.g., Azure ML, Azure Functions, Azure DevOps). Solid understanding of RESTful APIs, microservices, and CI/CD pipelines. Strong problem-solving and communication skills. Preferred Qualifications: Experience with LLMs, vector databases, and prompt engineering. Familiarity with containerization (Docker, Kubernetes). Knowledge of MLOps practices and tools. Exposure to Agile/Scrum methodologies.