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Senior Data Scientist with 11+ years building enterprise AI solutions, including LLM automation, RAG knowledge assistants, and agentic workflows. Experienced in designing end-to-end AI architectures with vector search, data pipelines, and real-time inference across Banking, Healthcare, Telecom, and Retail. Hands-on in production MLOps/LLMOps on AWS and Azure, delivering secure, observable AI platforms using Python, LangChain/LangGraph, Amazon Bedrock, SageMaker, OpenSearch, and streaming/batch data processing. Proficient in building predictive analytics, monitoring frameworks, and enterprise APIs that turn business needs into scalable AI products.…Senior Data Scientist with 11+ years building enterprise AI solutions, including LLM automation, RAG knowledge assistants, and agentic workflows. Experienced in designing end-to-end AI architectures with vector search, data pipelines, and real-time inference across Banking, Healthcare, Telecom, and Retail. Hands-on in production MLOps/LLMOps on AWS and Azure, delivering secure, observable AI platforms using Python, LangChain/LangGraph, Amazon Bedrock, SageMaker, OpenSearch, and streaming/batch data processing. Proficient in building predictive analytics, monitoring frameworks, and enterprise APIs that turn business needs into scalable AI products.

Navya Somannagari

Data Scientist, AI Engineer, Programmer, +2

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Senior Data Scientist with 11+ years building enterprise AI solutions, including LLM automation, RAG knowledge assistants, and agentic workflows. Experienced in designing end-to-end AI architectures with vector search, data pipelines, and real-time inference across Banking, Healthcare, Telecom, and Retail. Hands-on in production MLOps/LLMOps on AWS and Azure, delivering secure, observable AI platforms using Python, LangChain/LangGraph, Amazon Bedrock, SageMaker, OpenSearch, and streaming/batch data processing. Proficient in building predictive analytics, monitoring frameworks, and enterprise APIs that turn business needs into scalable AI products.…Senior Data Scientist with 11+ years building enterprise AI solutions, including LLM automation, RAG knowledge assistants, and agentic workflows. Experienced in designing end-to-end AI architectures with vector search, data pipelines, and real-time inference across Banking, Healthcare, Telecom, and Retail. Hands-on in production MLOps/LLMOps on AWS and Azure, delivering secure, observable AI platforms using Python, LangChain/LangGraph, Amazon Bedrock, SageMaker, OpenSearch, and streaming/batch data processing. Proficient in building predictive analytics, monitoring frameworks, and enterprise APIs that turn business needs into scalable AI products.

Available to hire

Senior Data Scientist with 11+ years building enterprise AI solutions, including LLM automation, RAG knowledge assistants, and agentic workflows. Experienced in designing end-to-end AI architectures with vector search, data pipelines, and real-time inference across Banking, Healthcare, Telecom, and Retail.

Hands-on in production MLOps/LLMOps on AWS and Azure, delivering secure, observable AI platforms using Python, LangChain/LangGraph, Amazon Bedrock, SageMaker, OpenSearch, and streaming/batch data processing. Proficient in building predictive analytics, monitoring frameworks, and enterprise APIs that turn business needs into scalable AI products.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

Work Experience

Senior Data Scientist at Morgan Stanley

January 1, 2022 - Present

Led development of an enterprise Generative AI platform for investment research, portfolio analysis, risk intelligence, regulatory compliance, and financial knowledge management using RAG, agentic AI, MCP, and LLM-based chat assistants on AWS. Architected and deployed scalable RAG solutions with Amazon Bedrock, LangChain/LlamaIndex, and vector search to retrieve reports, policies, compliance documents, and filings. Built MCP-enabled agents and multi-agent workflows using LangGraph/Bedrock Agents coordinated via Step Functions to perform planning, reasoning, retrieval, financial analysis, summarization, and workflow orchestration. Developed chatbot and multimodal document processing integrations using Bedrock, Lex, Comprehend, Kendra, Transcribe, Polly, and Rekognition. Engineered hybrid semantic search using OpenSearch vector search, Kendra, Titan embeddings, metadata filtering, and reranking. Implemented ingestion and indexing with chunking, metadata enrichment, classification, entity

AI Engineer at Boston Scientific

February 1, 2018 - December 31, 2021

Designed and deployed predictive and machine learning models for large-scale classification, regression, and analytics tasks using scikit-learn and gradient boosting algorithms. Built end-to-end ML pipelines including ingestion, preprocessing, feature engineering, evaluation, and deployment using Python and cloud ML platforms. Implemented scalable NLP pipelines (sentiment, entity recognition, text classification) and built chatbot solutions using Microsoft Bot Framework integrated with Azure services. Developed ML REST APIs (FastAPI/Flask) for real-time inference and containerized deployments using Docker/Kubernetes. Created workflow automation pipelines using Airflow and Azure Data Factory for ETL and retraining; applied explainable AI via SHAP/LIME and implemented monitoring for drift and accuracy. Built dashboards with Power BI/Plotly and supported governance through documentation and CI/CD with MLflow/Azure DevOps.

Machine Learning Engineer at T-Mobile

February 1, 2015 - January 31, 2018

Built predictive modeling and data processing pipelines for network analytics and customer behavior forecasting. Engineered high-performance feature extraction layers for telemetry and interaction datasets to support anomaly detection and predictive models. Implemented scalable ETL frameworks for structured/unstructured data and built RESTful APIs for real-time inference into internal customer support and network diagnostics portals. Designed and optimized relational schemas and wrote optimized SQL (MySQL/Oracle) for reporting performance. Applied statistical techniques and classification algorithms for sentiment analysis and churn prediction using social data feeds. Automated batch executions and synchronization using scheduling tools with performance logging; collaborated in Agile teams for feature and model validation and managed ML lifecycle from data ingestion to deployment and tuning.

Python Developer at Kroger

February 1, 2014 - August 31, 2015

Developed Python ETL scripts across multiple source systems to ensure accurate and timely reporting. Built SQL-based data validation frameworks to detect anomalies, inconsistencies, and missing values; created reusable modules for cleansing, feature engineering, and normalization. Wrote complex SQL queries, joins, nested subqueries, and stored procedures in SQL Server/Oracle for aggregation and operational analytics. Automated batch processing and scheduled reporting tasks to improve operational efficiency. Conducted exploratory data analysis and produced Excel dashboards/reports to visualize metrics and trends. Performed data profiling, reconciliation, and documentation of pipelines including source-to-target mappings and data dictionaries to improve transparency and maintainability; identified opportunities to reduce turnaround time through automation.