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I am Teja Chakilam, a Data Scientist and AI/ML Engineer with 6+ years delivering production AI systems across finance, healthcare, insurance, and retail. I specialize in GenAI, LLM orchestration, predictive modeling, and cloud-native MLOps on AWS, Azure, and GCP. I have led end-to-end ML and GenAI deployments, delivering impactful results such as 47% reduction in compliance analyst workload at Discover via an Agentic RAG system on AWS; 30% faster fraud-detection model delivery at EverNorth; 18–22% improvement in recommendation relevance at Flipkart, with real-time, 99.9% uptime. I enjoy building scalable, production-grade AI systems in collaborative cross-functional teams.…I am Teja Chakilam, a Data Scientist and AI/ML Engineer with 6+ years delivering production AI systems across finance, healthcare, insurance, and retail. I specialize in GenAI, LLM orchestration, predictive modeling, and cloud-native MLOps on AWS, Azure, and GCP. I have led end-to-end ML and GenAI deployments, delivering impactful results such as 47% reduction in compliance analyst workload at Discover via an Agentic RAG system on AWS; 30% faster fraud-detection model delivery at EverNorth; 18–22% improvement in recommendation relevance at Flipkart, with real-time, 99.9% uptime. I enjoy building scalable, production-grade AI systems in collaborative cross-functional teams.

Teja Chakilam

Data Scientist, AI Engineer, Developer, +5

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I am Teja Chakilam, a Data Scientist and AI/ML Engineer with 6+ years delivering production AI systems across finance, healthcare, insurance, and retail. I specialize in GenAI, LLM orchestration, predictive modeling, and cloud-native MLOps on AWS, Azure, and GCP. I have led end-to-end ML and GenAI deployments, delivering impactful results such as 47% reduction in compliance analyst workload at Discover via an Agentic RAG system on AWS; 30% faster fraud-detection model delivery at EverNorth; 18–22% improvement in recommendation relevance at Flipkart, with real-time, 99.9% uptime. I enjoy building scalable, production-grade AI systems in collaborative cross-functional teams.…I am Teja Chakilam, a Data Scientist and AI/ML Engineer with 6+ years delivering production AI systems across finance, healthcare, insurance, and retail. I specialize in GenAI, LLM orchestration, predictive modeling, and cloud-native MLOps on AWS, Azure, and GCP. I have led end-to-end ML and GenAI deployments, delivering impactful results such as 47% reduction in compliance analyst workload at Discover via an Agentic RAG system on AWS; 30% faster fraud-detection model delivery at EverNorth; 18–22% improvement in recommendation relevance at Flipkart, with real-time, 99.9% uptime. I enjoy building scalable, production-grade AI systems in collaborative cross-functional teams.

Available to hire

I am Teja Chakilam, a Data Scientist and AI/ML Engineer with 6+ years delivering production AI systems across finance, healthcare, insurance, and retail. I specialize in GenAI, LLM orchestration, predictive modeling, and cloud-native MLOps on AWS, Azure, and GCP.

I have led end-to-end ML and GenAI deployments, delivering impactful results such as 47% reduction in compliance analyst workload at Discover via an Agentic RAG system on AWS; 30% faster fraud-detection model delivery at EverNorth; 18–22% improvement in recommendation relevance at Flipkart, with real-time, 99.9% uptime. I enjoy building scalable, production-grade AI systems in collaborative cross-functional teams.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Data Scientist (GEN AI) at Huntington National Bank

January 1, 2023 - Present

Implemented automated report generation systems with Generative AI and utilized LLMs like Llama 3 for text generation and data understanding. Developed scalable Graph RAG pipelines using knowledge graphs and vector databases, enhancing retrieval accuracy by 35%. Built OCR pipelines increasing document digitization efficiency by 40% and fine-tuned NLU models using transformer architectures to improve AI-driven applications. Designed autonomous AI agents for multi-turn task delegation, reducing human intervention by 40%. Created domain-specific chatbots and deployed AI-driven workflows across finance and retail. Leveraged AWS SageMaker and Bedrock for cloud model deployment, implemented scalable machine learning architectures, and led presales efforts contributing to significant revenue growth.

Machine Learning Engineer (Data Scientist) at Ever North Health Services

December 31, 2022 - July 31, 2025

Utilized Python libraries for data manipulation and modeling in healthcare fraud detection. Engineered features from claims data and applied machine learning algorithms and deep learning models, improving predictive accuracy by 30%. Developed interactive Tableau and Power BI dashboards for real-time business insights. Handled imbalanced datasets using SMOTE and ensemble techniques and deployed models using Azure services. Applied CI/CD pipelines and Agile methodologies to improve time-to-market. Ensured model explainability and maintained performance tracking with monitoring mechanisms.

Data Scientist at HDFC Life

July 31, 2021 - July 31, 2025

Cleaned, preprocessed, and analyzed customer data to build predictive models for insurance product purchase likelihood and churn probability. Conducted exploratory data analysis, customer segmentation, and marketing campaign design. Developed ETL pipelines via AWS Glue, optimized SQL queries, and leveraged AWS SageMaker for hyperparameter tuning. Created interactive Power BI dashboards and refined predictive models based on customer feedback. Documented processes for reproducibility and knowledge sharing.

Python Developer at Flipkart

December 31, 2019 - July 31, 2025

Implemented data preprocessing and feature extraction pipelines for recommendation systems using Python. Developed collaborative and content-based filtering algorithms, integrating hybrid recommendation systems. Employed containerization and orchestration technologies like Docker and Kubernetes. Integrated Azure Blob Storage, secure API pipelines, and deployed infrastructure using Terraform and ARM templates. Optimized large-scale data pipelines using Snowflake and monitored system health for performance and reliability.

Data Scientist (GEN AI) at Huntington National Bank

January 1, 2023 - Present

Implemented an automated report generation system using Generative AI and large language models such as Llama 3 with Retrieval-Augmented Generation frameworks. Developed scalable Graph RAG pipelines using knowledge graphs and vector databases for enhanced contextual retrieval accuracy by 35%. Engineered data pipelines for efficient preprocessing and designed modular report generation strategies. Integrated LangChain for NLP tasks like data extraction, summarization, and fact-checking. Developed OCR pipelines to extract unstructured data from PDFs and scanned documents, improving digitization efficiency by 40%. Utilized GANs for synthetic text generation, leading to a 20% model accuracy improvement. Built autonomous AI agents using Microsoft’s Autogen framework for multi-turn task delegation, reducing human intervention by 40%. Led POCs for AI-driven workflows and integrated multi-agent orchestration systems using LangGraph and n8n. Deployed solutions on cloud platforms with Kubernete

Machine Learning Engineer (Data Scientist) at Ever North Health Services

December 31, 2022 - July 31, 2025

Exploited Python libraries for data manipulation, visualization, and modeling of healthcare claims data to detect fraud and customer segmentation. Applied statistical and machine learning techniques including logistic regression, decision trees, CNNs, RNNs, and advanced ensemble methods. Developed Tableau dashboards and Power BI reports to provide real-time insights for senior management. Employed dimensionality reduction and dealt with imbalanced data techniques to improve model accuracy. Developed deep learning models using TensorFlow and Keras, increasing predictive accuracy by 30%. Deployed models in Azure cloud environments with CI/CD automated pipelines and utilized NLP for contextual information retrieval improving system performance by 30%. Collaborated across teams adopting Agile methodologies to improve time-to-market for new AI features by 30%.

Data Scientist at HDFC Life

July 31, 2021 - July 31, 2025

Conducted data cleaning, preprocessing, and exploratory data analysis for customer segmentation and predictive modeling in insurance domain. Used clustering algorithms to segment customers and classification models to predict behaviors like product purchase and churn. Developed and deployed Power BI dashboards to translate complex data insights for key stakeholders. Created and optimized ETL pipelines using AWS Glue and SQL queries to process large datasets efficiently. Leveraged AWS SageMaker for building and optimizing ML models achieving 15% improvement in predictions. Analyzed campaign feedback for sentiment and continuously refined models based on new data and insights.

Python Developer at Flipkart

December 31, 2019 - July 31, 2025

Developed data preprocessing pipelines and feature extraction scripts for recommendation systems using Python. Implemented collaborative and content-based filtering algorithms for product recommendation. Integrated recommendation systems into e-commerce platform and supported A/B testing to refine model performance. Used containerization technologies and managed secure API pipelines for deployment of recommendation services with Azure cloud infrastructure. Optimized Snowflake data pipelines for improved machine learning workflow efficiency and ensured system reliability through monitoring and logging.

Data Scientist (GEN AI) at Huntington National Bank

January 1, 2023 - Present

Implemented automated report generation systems using Generative AI and LLMs like Llama 3, incorporating techniques like Retrieval-Augmented Generation (RAG) and knowledge graphs to enhance model accuracy by 35%. Developed scalable Graph RAG pipelines leveraging vector databases (Neo4j, Pinecone), engineered OCR pipelines to digitize unstructured documents improving data extraction efficiency by 40%, and fine-tuned advanced NLP models including transformers (BERT, GPT). Designed autonomous AI multi-agent systems with Microsoft’s Autogen framework, reducing human intervention by 40%. Delivered POCs enhancing AI and workflow automation with tools like LangChain, CrewAI, LangGraph, MCP, and n8n. Leveraged cloud platforms (AWS, Azure) for deploying models and managed scalable Kubernetes clusters. Contributed to 25%+ revenue growth through presales and optimized data visualization with Tableau and Power BI for business insights.

Machine Learning Engineer (Data Scientist) at Ever North Health Services

December 31, 2022 - July 31, 2025

Utilized Python libraries (pandas, NumPy, scikit-learn) for data manipulation, preprocessing, modeling, and visualization of healthcare claims data. Applied classification and anomaly detection algorithms (logistic regression, decision trees, isolation forest) for fraud detection, enhanced with CNN and RNN architectures for sequential data tasks. Engineered features and addressed class imbalance with SMOTE. Developed and deployed models using TensorFlow and Keras, improving predictive accuracy by 30%. Designed NLP-integrated information retrieval systems, boosting retrieval accuracy by 30%. Leveraged Microsoft Azure for scalable deployment, managed CI/CD pipelines via Azure DevOps, and applied Agile methodologies to reduce time-to-market by 30%. Created Tableau and Power BI dashboards to provide real-time business insights and contributed to cross-functional team initiatives.

Data Scientist at HDFC Life

July 31, 2021 - July 31, 2025

Cleaned and preprocessed customer data for machine learning including feature engineering and encoding. Conducted exploratory data analysis and customer segmentation using clustering algorithms. Developed predictive models for customer behavior forecasting using classification algorithms like logistic regression and random forests. Created Power BI dashboards for actionable business insights. Developed ETL pipelines with AWS Glue and optimized SQL queries for data retrieval. Applied AWS SageMaker for model training and hyperparameter tuning, improving prediction accuracy by 15%. Analyzed marketing campaign effectiveness and sentiment analysis, refining models and campaign strategies over time. Documented all processes to ensure reproducibility and team knowledge sharing.

Python Developer at Flipkart

December 31, 2019 - July 31, 2025

Implemented data preprocessing pipelines and feature extraction scripts for user interaction data using Python. Developed collaborative filtering and content-based recommendation algorithms, integrated hybrid recommendation systems, and performed model evaluation. Supported A/B testing and incorporated user feedback to improve recommendations. Used Azure services for secure API data pipelines and deployment. Designed and deployed infrastructure with Terraform and Azure Resource Manager templates. Optimized large-scale data pipelines in Snowflake and monitored recommendation system performance. Collaborated with cross-functional teams to integrate recommendation systems into Flipkart's platform and ensured system reliability and uptime.

Data Scientist – GenAI at Cisco (BEACON / Sales AI Assistant)

May 1, 2025 - Present

Built and stabilized an enterprise GenAI Sales Assistant using LangChain and LangGraph to generate sales pitches, outreach emails, and solution recommendations supporting real-world sales workflows. Designed and optimized RAG pipelines with enterprise knowledge sources, improving grounding and factual accuracy by 30% while reducing hallucinations. Implemented multi-agent orchestration with supervisor and task-specific agents in LangGraph, reducing agent misrouting and fallback errors by 35%. Tuned retrieval depth, chunking strategies, and domain inclusion/exclusion logic, increasing stakeholder acceptance scores by 25%. Converted sequential LLM calls to parallel and asynchronous execution in LangChain, cutting end-to-end latency by 40% under production load. Owned end-to-end production stability — debugging context failures, agent routing errors, and API rate limits — achieving 99.9% availability at launch.

AI/ML Engineer at Huntington National Bank

January 1, 2023 - May 1, 2025

Built an automated GenAI reporting system using Llama 3 with OCR pipelines (Tesseract, AWS Textract), cutting report turnaround time by 40% and boosting unstructured document processing efficiency by 40%. Designed and deployed a RAG architecture (MARGE) combining knowledge graphs (Neo4j) and vector databases (Pinecone), improving domain-specific retrieval accuracy by 35%. Developed multi-step autonomous AI agents using LangGraph, LangChain, AutoGen, and CrewAI for extraction, summarisation, fact-checking, and delegation, reducing manual intervention by 40%. Fine-tuned LLMs with LoRA/QLoRA and applied GAN-based synthetic data generation, improving NLU performance by 20% and enhancing contextual response quality. Implemented prompt evaluation and tracing with LangSmith and RAGAS to ensure consistency and reliability across all multi-agent workflows. Deployed production AI systems on AWS (S3, Lambda, ECS, SageMaker) with Docker containerisation and AWS Glue ETL, enabling real-time analyti

Machine Learning Engineer at EverNorth Health Services

March 1, 2022 - December 1, 2022

Led end-to-end ML development on large-scale healthcare claims data using Python (Pandas, NumPy, Scikit-learn), engineering features across diagnosis codes, procedure codes, provider IDs, and claim amounts for fraud detection. Applied classical ML and anomaly detection — logistic regression, decision trees, isolation forest, one-class SVM — with SMOTE resampling to improve detection reliability on imbalanced data. Built and productionised deep learning models (TensorFlow/Keras) using CNNs for feature extraction and RNNs for sequential claims patterns, increasing predictive accuracy by 30%. Deployed real-time scoring APIs with FastAPI on Azure ML, AKS, and Databricks with CI/CD pipelines in Azure DevOps, reducing time-to-market by 30%. Ensured regulatory-ready model explainability using SHAP and LIME, and improved SQL data extraction and transformation query efficiency by 30%. Delivered executive fraud trend dashboards via Tableau and Power BI tracking real-time KPIs for senior stak

Data Scientist at HDFC Life Insurance

January 1, 2020 - July 1, 2021

Cleaned, standardised, and encoded large-scale customer and policy data, performing EDA and statistical analysis to surface behavioural patterns and key business drivers. Segmented customers using k-means and hierarchical clustering, profiling segments by engagement and translating insights into actionable targeting strategies. Built churn and purchase propensity models (logistic regression, decision trees, random forests), increasing predictive accuracy by 15% via feature engineering and SageMaker hyperparameter tuning. Designed and optimised targeted marketing campaigns, tracking conversion and response KPIs and iterating strategies based on real-world performance. Developed ETL pipelines with AWS Glue, S3, and Snowflake, and delivered Power BI dashboards cutting data processing time by 30%.