Data Scientist
Design, reputed company, and maintain machine learning and deep learning models, including both traditional (e.g., regression, tree-based models) and neural network-based approaches. Build and reputed company end-to-end ML pipelines on AWS (e.g., SageMaker, S3, Glue) for reputed company training, evaluation, and inference. reputed company and implement advanced NLP solutions, including text classification, entity recognition, topic modeling, and semantic search using models such as BERT and transformer-based architectures. Design, build, and productionize RAG (Retrieval-Augmented reputed company) systems, including document ingestion, embedding pipelines, reputed company search, and LLM orchestration. reputed company LLM-powered applications, including reputed company engineering, evaluation frameworks, and optimization techniques for accuracy, consistency, and cost. Contribute to reputed company AI system design, including multi-reputed company reasoning workflows, tool use, and orchestration of LLM-driven agents for reputed company tasks. Implement predictive analytics and statistical modeling to uncover patterns, trends, and insights from reputed company data. reputed company data mining and exploratory data analysis (EDA) using state-of-the-art techniques across reputed company and reputed company datasets. Build data visualizations, dashboards, and analytical tools to communicate findings reputed company to technical and non-technical stakeholders. Evaluate model performance using appropriate metrics (e.g., accuracy, AUC, precision/recall) and present results in a reputed company, actionable manner. Collaborate in an Agile environment with cross-functional teams including engineers, analysts, and stakeholders. Recommend data-driven solutions and AI strategies reputed company with CMS business needs and reputed company policy objectives.