Data Scientist

Key Responsibilities: • Develop and implement machine learning models and algorithms. • Work closely with project stakeholders to understand requirements and translate them into deliverables. • Utilize statistical and machine learning techniques to analyze and interpret complex data sets. • Stay updated with the latest advancements in AI/ML technologies and methodologies. • Collaborate with cross-functional teams to support various AI/ML initiatives. Qualifications: • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. • Strong understanding of machine learning , deep learning and Generative AI concepts. Preferred Skills: • Experience in machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, Deep Learning stack, NLP using python • Strong knowledge and experience in Generative AI/ LLM based development. • Strong experience working with key LLM models APIs (e.g. AWS Bedrock, Azure Open AI/ OpenAI) and LLM Frameworks (e.g. LangChain, LlamaIndex). • Experience with cloud infrastructure for AI/Generative AI/ML on AWS, Azure. • Expertise in building enterprise grade, secure data ingestion pipelines for unstructured data – including indexing, search, and advance retrieval patterns. • Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets. • Proficiency in generating and working with text embeddings with understanding of embedding spaces and their applications in semantic search and information. retrieval. • Experience with RAG concepts and fundamentals (VectorDBs, AWS OpenSearch, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with Generative AI models. • Knowledge of training and fine-tuning Foundation Models (Athropic, Claud , Mistral, etc.), including multimodal inputs and outputs. • Proficiency in Python, TypeScript, NodeJS, ReactJS (and equivalent) and frameworks. (e.g., pandas, NumPy, scikit-learn), Glue crawler, ETL • Experience with data visualization tools (e.g., Matplotlib, Seaborn, Quicksight). • Knowledge of deep learning frameworks (e.g., TensorFlow, Keras, PyTorch). • Experience with version control systems (e.g., Git, CodeCommit). Good to have Skills • Knowledge and Experience in building knowledge graphs in production. • Understanding of multi-agent systems and their applications in complex problemsolving scenarios