Data Scientist

Must have• 3–4 years of experience building AI/ML applications with strong Python and software engineering skills.• Strong proficiency in Python.• Hands-on experience with:o Understanding of AI system design, evaluation, monitoring, and performanceoptimization.o Experience developing, deploying, and maintaining production AIapplications.o Strong software engineering fundamentals, including clean code, modular design,debugging, and testing.o RAG architectures• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.• Good understanding of NLP concepts.• Familiarity with API development and integration.• Ability to work independently as well as in collaborative team environments.Good to have• Experience with vector databases such as Pinecone, Weaviate, FAISS, ChromaDB.• Knowledge of cloud platforms such as AWS, Azure, or GCP.• Experience with Docker, and deployment pipelines.• Exposure to fintech products, platforms, or domain-specific use cases.Roles & Responsibilities• Design scalable, reliable AI systems with a focus on production readiness, maintainability, and performance.• Perform root cause analysis and debugging of AI pipelines to improve accuracy, consistency, and reliability.• Develop automated evaluation, validation, and testing strategies for AI applications.• Design reliable LLM workflows using structured outputs, validation, retrieval, and business rules.• Create and maintain RAG pipelines and AI agent frameworks.• Perform data analysis, model evaluation, and performance optimization.• Develop APIs and integrate AI solutions into existing products and platforms.• Collaborate with cross-functional teams including engineering, and business stakeholders to define AI use cases and deliver solutions.• Monitor, troubleshoot, and continuously improve deployed AI systems.