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I am an AI/ML and data engineering expert with 10+ years of experience designing and deploying large-scale ETL pipelines, LLM systems, RAG workflows, NLP models, and enterprise analytics platforms across insurance, healthcare, telecom, retail, capital markets, and manufacturing. I design and deploy scalable, cloud-native data pipelines, LLM systems, and governance frameworks with a strong emphasis on data quality, lineage, and observability to enable trusted AI. I thrive in cross-functional teams and enjoy turning complex business problems into data-driven solutions, delivering production-grade AI and data platforms across multi-cloud environments while upholding governance, security, and compliance requirements.…I am an AI/ML and data engineering expert with 10+ years of experience designing and deploying large-scale ETL pipelines, LLM systems, RAG workflows, NLP models, and enterprise analytics platforms across insurance, healthcare, telecom, retail, capital markets, and manufacturing. I design and deploy scalable, cloud-native data pipelines, LLM systems, and governance frameworks with a strong emphasis on data quality, lineage, and observability to enable trusted AI. I thrive in cross-functional teams and enjoy turning complex business problems into data-driven solutions, delivering production-grade AI and data platforms across multi-cloud environments while upholding governance, security, and compliance requirements.

Sai Divya Eadara

Data Scientist, AI Engineer, AI Developer, +2

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I am an AI/ML and data engineering expert with 10+ years of experience designing and deploying large-scale ETL pipelines, LLM systems, RAG workflows, NLP models, and enterprise analytics platforms across insurance, healthcare, telecom, retail, capital markets, and manufacturing. I design and deploy scalable, cloud-native data pipelines, LLM systems, and governance frameworks with a strong emphasis on data quality, lineage, and observability to enable trusted AI. I thrive in cross-functional teams and enjoy turning complex business problems into data-driven solutions, delivering production-grade AI and data platforms across multi-cloud environments while upholding governance, security, and compliance requirements.…I am an AI/ML and data engineering expert with 10+ years of experience designing and deploying large-scale ETL pipelines, LLM systems, RAG workflows, NLP models, and enterprise analytics platforms across insurance, healthcare, telecom, retail, capital markets, and manufacturing. I design and deploy scalable, cloud-native data pipelines, LLM systems, and governance frameworks with a strong emphasis on data quality, lineage, and observability to enable trusted AI. I thrive in cross-functional teams and enjoy turning complex business problems into data-driven solutions, delivering production-grade AI and data platforms across multi-cloud environments while upholding governance, security, and compliance requirements.

Available to hire

I am an AI/ML and data engineering expert with 10+ years of experience designing and deploying large-scale ETL pipelines, LLM systems, RAG workflows, NLP models, and enterprise analytics platforms across insurance, healthcare, telecom, retail, capital markets, and manufacturing. I design and deploy scalable, cloud-native data pipelines, LLM systems, and governance frameworks with a strong emphasis on data quality, lineage, and observability to enable trusted AI.

I thrive in cross-functional teams and enjoy turning complex business problems into data-driven solutions, delivering production-grade AI and data platforms across multi-cloud environments while upholding governance, security, and compliance requirements.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Gen AI Engineer at MetLife

May 1, 2024 - October 31, 2025

Architected an end-to-end GenAI claims automation platform integrating Python (Flask), .NET 6, and React.js to process 10K+ claims daily for real-time automation and insights. Built RESTful microservices for document ingestion, NLP-based claim parsing, and model inference. Implemented Retrieval-Augmented Generation (RAG) pipelines with LangChain and vector databases; fine-tuned LLMs (GPT-4, Claude) using LoRA/PEFT for domain-specific narratives. Containerized modules with Docker, deployed on Kubernetes (AKS), and automated releases with GitHub Actions and Terraform. Secured authentication via Azure AD B2C and JWT; optimized inference with Redis caching and load balancing. Designed scalable data pipelines on AWS S3/Lambda/Step Functions and integrated with Snowflake marts. Created analytics dashboards (Power BI Embedded) and enhanced system observability (Prometheus, Azure Monitor, CloudWatch).

AI/ML Data Scientist at Johnson & Johnson

April 1, 2024 - April 1, 2024

Led development of an AI-driven document intelligence platform for 50K+ documents, enabling automated classification, semantic search, and knowledge extraction. Built NLP pipelines with Hugging Face transformers (BERT/RoBERTa/DeBERTa); engineered hybrid search using vector embeddings with Google Vector Search and Azure AI Search. Fine-tuned domain LLMs via Vertex AI and integrated with Azure Foundry/Copilot Studio. Implemented MLOps pipelines (SageMaker, Lambda, Step Functions); designed REST microservices (Flask/FastAPI) and Kubernetes-based deployments for low-latency inference. Built PySpark EMR data processing, Snowflake warehousing, and ETL pipelines with Glue; delivered Power BI dashboards. Established model governance and drift monitoring.

AI/ML Engineer at Johnson&Johnson

February 1, 2022 - April 1, 2024

Designed and delivered LLM-powered conversational AI platforms on AWS to enable leaders to query enterprise datasets via natural language. Fine-tuned and deployed chatbots using AWS Bedrock (Anthropic, Titan, LLama models) with RAG pipelines, built multi-agent architectures (retrieval, reasoning, validation, orchestration), and created SQL-generation agents to surface KPIs. Implemented vector search and document intelligence workflows with FAISS, OpenSearch, and Kendra; built enterprise search and document Q&A systems; established LLM orchestration with Step Functions; automated evaluation and retraining pipelines; ensured governance and compliance for healthcare data.

ML Data Scientist at AT&T

January 1, 2022 - January 1, 2022

Designed an AI-powered fraud detection platform across mortgage datasets; built and validated models using Python/R for fraud detection, loan default, and credit risk. Addressed class imbalance with SMOTE and resampling; applied feature engineering and dimensionality reduction; deployed Spark-based pipelines on AWS EMR and integrated with Kafka for real-time ingestion. Delivered interpretable models, dashboards, and ROI analyses; established model governance and drift monitoring; collaborated with Data Science and Engineering teams in an Agile environment.

AI/ML Engineer at AT&T

November 1, 2019 - January 1, 2022

Designed and implemented AI/ML analytics and conversational data solutions on Microsoft Azure. Built Azure-based data pipelines (ADLS, Azure Databricks, Data Factory), prepared LLM-ready datasets for RAG and semantic search, and engineered semantic analytical layers aligned with business KPIs. Developed scalable PySpark ETL/ELT pipelines, reusable Python preprocessing frameworks with profiling and lineage, and feature engineering for improved model performance. Developed and validated ML models (Gradient Boosting, Random Forest, Logistic Regression) for fraud, customer analytics, and risk scoring; implemented distributed ML pipelines with Spark MLlib; automated KPI reporting and API exposure for downstream applications; established data quality and governance practices.

Data Scientist at The Sherwin Williams

October 1, 2019 - October 1, 2019

Architected a modular service layer ingesting daily store SKU data, historical sales, and external indicators to drive demand forecasting. Exposed predictions via REST APIs for inventory alerts and color-trend suggestions; built a React frontend for visualization. Implemented end-to-end data pipelines with Apache Spark and AWS Glue; developed forecasting models (XGBoost, LSTM) with substantial accuracy improvements; enabled auto-scaling with Docker/Kubernetes and deployment of SageMaker endpoints. Built a Snowflake-based data warehouse with star/snowflake schemas; developed Power BI dashboards; configured monitoring with Prometheus and CloudWatch; integrated Cognito authentication and CI/CD via GitHub Actions. Collaborated with supply-chain teams to incorporate live data feeds and conducted A/B testing to optimize performance.

Data Engineer at The Sherwin Williams

September 1, 2017 - October 1, 2019

Designed and implemented retail-focused AI solutions leveraging store-level SKU data, sales history, pricing trends, and operational signals to inform leadership decisions. Led development of a leadership-facing AI chatbot mapping natural language questions to SKU catalogs, merchandising KPIs, inventory metrics, and store performance insights. Built Python/.NET microservices translating executive questions into SQL across Redshift and data marts; created Spark/AWS Glue ETL/ELT pipelines; developed forecasting models (XGBoost, LSTM) with validation and lineage checks; built real-time recommendations and ofﬂine analytics; containerized AI and data services with Docker and deployed on AWS EKS; implemented Kafka ingestion, monitoring, and governance; automated CI/CD with GitHub Actions and Terraform.

Associate Data Scientist at Kiro Info Solutions

August 1, 2017 - August 1, 2017

Developed an AI-driven customer analytics platform for churn prediction and fraud detection; built logistic regression, random forest, and gradient boosting models; explored NLP via Word2Vec/GloVe; delivered Tableau dashboards and real-time monitoring with Kubernetes-based microservices. Implemented data pipelines and data warehousing on AWS (S3/Redshift) and integrated SageMaker endpoints; implemented model explainability and reporting; collaborated with cross-functional teams to deliver ROI insights and business impact.

Associate Data Scientist at Kiro Info Solutions

June 1, 2015 - August 1, 2017

Designed an AI-driven customer analytics platform for churn prediction, fraud detection, and service efficiency. Built ML models (Logistic Regression, Random Forest, Gradient Boosting) and applied NLP on transcripts (Word2Vec, GloVe, TF-IDF, BERT) for sentiment and intent. Performed data preprocessing, feature engineering, and dimensionality reduction; created Tableau dashboards and Power BI reports; developed Kubernetes-deployed AI microservices for scalable model serving; established real-time data ingestion pipelines and data quality rules; delivered insights to stakeholders and collaborated with cross-functional teams.