Available to hire
I am a Lead Full Stack Data Scientist with expertise in developing and deploying machine learning models across diverse domains. Skilled in predictive analytics, NLP, and deep learning, I optimize business processes and improve decision-making. With a strong background in cloud technologies such as AWS and Azure, data engineering, and building scalable solutions with Docker and Kubernetes, I am committed to driving business success through effective use of data science and AI technologies.
I am experienced in MLOps practices, automating machine learning workflows with Kubeflow and MLFlow, and deploying AI-driven solutions using AWS Bedrock for generative AI tasks. My collaborative approach helps define AI product requirements, optimize cloud infrastructure, and streamline workflows to deliver impactful AI solutions.
Skills
Language
English
Fluent
Work Experience
Lead AI Machine Learning Engineer at State Farm
April 1, 2023 - PresentLed the development of machine learning models using Python, TensorFlow, and scikit-learn to predict customer claims, increasing decision-making accuracy by 30%. Deployed scalable real-time predictive models using AWS SageMaker, Kubernetes, and Docker, reducing deployment time by 25%. Optimized cloud infrastructure with AWS Lambda, AWS S3, Azure ML, and AWS Bedrock, lowering costs by 20%. Automated model training pipelines via Jenkins, GitLab, and Kubeflow, halving model update times. Built AI-driven recommendation systems improving customer engagement by 20%. Integrated Apache Kafka and Spark for real-time data streaming and large-scale processing. Streamlined workflows with Apache Airflow and automated infrastructure with Terraform, enhancing scalability and reducing provisioning time by 30%.
AI - ML Engineer/Senior Data Scientist at AT&T
April 1, 2023 - July 25, 2025Developed machine learning models forecasting network traffic with Python, scikit-learn, and Keras, reducing service disruptions by 20%. Deployed real-time analytics models using AWS SageMaker, Docker, and Kubernetes, cutting deployment time by 30%. Optimized cloud infrastructure and reduced operational costs by 15%. Automated CI/CD pipelines with Jenkins, GitLab, and Kubeflow, accelerating model updates by 40%. Created AI-driven anomaly detection systems improving uptime by 15%, collaborated on predictive maintenance tools enhancing workflows by 25%. Handled large-scale data processing with Apache Spark and streaming with Kafka. Automated ETL pipelines with Airflow for improved data accessibility and decision-making.
Senior ML Engineer at HMS
January 1, 2023 - July 25, 2025Built predictive analytics models for healthcare data with Python, TensorFlow, and scikit-learn, improving patient outcome predictions by 25%. Deployed scalable models using AWS SageMaker and Docker, cutting deployment time by 30%. Automated data pipelines with Apache Airflow and AWS Lambda, reducing processing time by 40%. Led development of an anomaly detection system using TensorFlow and Keras, enhancing critical health event detection by 20%. Developed NLP models for medical record processing achieving 95% accuracy. Utilized Spark for big data healthcare processing and Kafka for real-time data streaming, improving data availability and decision-making speed.
Senior Data Scientist/ML Architect at FCA Fiat Chrysler Automobiles
January 1, 2022 - July 25, 2025Developed vehicle maintenance prediction models with Python, scikit-learn, and XGBoost, reducing downtime by 15%. Built supply chain predictive models leveraging AWS SageMaker and Docker, improving inventory management and delivery timelines. Designed NLP models for customer feedback analysis, increasing satisfaction by 18%. Deployed deep learning models analyzing driving patterns for vehicle safety, improving reliability by 10%. Optimized data pipelines with Apache Spark and Hadoop, decreasing analysis time by 40%. Created AI-driven recommendation systems to personalize marketing, boosting engagement by 25%. Implemented real-time data pipelines using Kafka and Lambda for predictive maintenance. Led AI/ML integration initiatives ensuring scalable solutions across operations.
Data Engineer (Systems Analyst) at Tata Consultancy Services
August 31, 2015 - July 25, 2025Constructed ETL pipelines utilizing SQL, Python, and Apache Nifi, improving data quality and reducing processing time by 30%. Created machine learning models with scikit-learn and TensorFlow to support predictive analytics, enhancing decision-making by 20%. Built customer behavior and market trend data models to inform business strategies. Developed custom dashboards with Power BI and Tableau providing real-time insights. Collaborated cross-functionally to define data requirements and predictive models, improving workflows by 25%. Executed data validation and cleansing to ensure high data accuracy. Automated recurring data tasks via Python scripts, decreasing manual effort by 40%. Delivered data-driven insights to influence performance improvements across business units.
Lead AI Machine Learning Engineer at State Farm
April 1, 2023 - PresentLed development of machine learning models using Python, TensorFlow, and scikit-learn to predict customer claims, achieving a 30% increase in decision-making accuracy and operational efficiency. Deployed real-time predictive models with AWS SageMaker, Kubernetes, and Docker, enhancing scalability and reducing deployment time by 25%. Optimized cloud infrastructure with AWS Lambda, AWS S3, Azure Machine Learning, and AWS Bedrock, lowering operational costs by 20% while improving system performance. Automated model training and feature engineering processes using CI/CD pipelines with Jenkins, GitLab, and Kubeflow, decreasing model update times by 50%. Collaborated with cross-functional teams to define AI product requirements and integrate RESTful APIs and GraphQL, increasing workflow efficiency by 30%. Developed AI-driven recommendation systems with PyTorch and TensorFlow, improving customer engagement by 20%. Conducted model performance reviews and retraining with Kubernetes-managed pipe
AI - ML Engineer / Senior Data Scientist at AT&T
April 1, 2023 - September 4, 2025Developed machine learning models with Python, scikit-learn, and Keras to forecast network traffic patterns and enhance system reliability, resulting in a 20% reduction in service disruptions. Deployed real-time analytics models using AWS SageMaker, Docker, and Kubernetes, improving model scalability and reducing deployment time by 30%. Optimized cloud infrastructure with AWS Lambda, Azure ML, and AWS Bedrock, reducing operational costs by 15% and enhancing system performance across network operations. Implemented automated model training and feature engineering pipelines with CI/CD tools such as Jenkins, GitLab, and Kubeflow, speeding model updates by 40% and improving overall delivery efficiency. Collaborated with network engineers to define AI-driven product requirements for predictive maintenance and anomaly detection, improving operational workflows by 25%. Developed AI-based anomaly detection systems using TensorFlow and PyTorch to detect network issues earlier and improve system
Senior ML Engineer at HMS
January 1, 2023 - September 4, 2025Developed machine learning models using Python, TensorFlow, and scikit-learn to enhance predictive analytics for healthcare data, improving patient outcome predictions by 25%. Deployed models with AWS SageMaker and Docker, improving model scalability and reducing deployment time by 30%. Optimized data pipelines using Apache Airflow and AWS Lambda, automating healthcare data flow and reducing processing time by 40%. Led development of an anomaly detection system for patient monitoring using TensorFlow and Keras, improving detection of critical health events by 20%. Collaborated with healthcare teams to define product requirements and integrate AI solutions, contributing to a 15% increase in team efficiency and project turnaround times. Developed and deployed NLP models for processing unstructured medical records, achieving 95% accuracy in data extraction tasks. Conducted regular model evaluations and fine-tuning, ensuring 85%+ accuracy in real-world applications and improving model reli
Senior Data Scientist / ML Architect at FCA Fiat Chrysler Automobiles
January 1, 2022 - September 4, 2025Developed machine learning models using Python, scikit-learn, and XGBoost to predict vehicle maintenance needs, resulting in a 15% reduction in downtime and improved operational efficiency. Built predictive models to enhance supply chain operations and optimize inventory management leveraging AWS SageMaker and Docker, reducing stock-outs by 20% and improving delivery timelines. Designed and implemented NLP models for analyzing customer feedback, enabling targeted product enhancements and improving customer satisfaction by 18%. Developed and deployed deep learning models using TensorFlow and Keras to analyze driving patterns and optimize vehicle safety features, improving vehicle reliability by 10%. Optimized data pipelines with Apache Spark and Hadoop, enabling processing of large automotive datasets, cutting analysis time by 40% and improving insights delivery speed. Created AI-driven recommendation systems to personalize vehicle marketing strategies, increasing customer engagement by
Data Engineer (Systems Analyst) at Tata Consultancy Services
August 1, 2015 - September 4, 2025Developed ETL pipelines using SQL, Python, and Apache NiFi to automate data ingestion, transformation, and cleaning, improving data quality and reducing processing time by 30%. Designed and implemented machine learning models for predictive analytics leveraging scikit-learn and TensorFlow to derive insights from large datasets, improving decision-making efficiency by 20%. Built data models to analyze customer behavior and market trends, using statistical analysis and data visualization to guide business strategy and optimize operations. Created custom dashboards and interactive reports using Power BI and Tableau, providing real-time insights and enhancing data accessibility for stakeholders. Collaborated with cross-functional teams to define data requirements and build predictive models aligned with business goals, improving operational workflows by 25%. Conducted data validation and cleaning to ensure high-quality, accurate data, improving reliability of data-driven insights for key b
Education
Master of Science at Syracuse University
August 1, 2015 - May 31, 2017Bachelor of Technology at Acharya Nagarjuna University
August 1, 2010 - May 31, 2014Master of Science in Engineering Management at Syracuse University
August 1, 2015 - May 1, 2017Bachelor of Technology in Engineering at Acharya Nagarjuna University
August 1, 2010 - May 1, 2014Qualifications
Industry Experience
Financial Services, Healthcare, Manufacturing, Telecommunications, Software & Internet, Transportation & Logistics
Skills
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