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I am a Data Scientist and GenAI Engineer with over 10 years of experience specializing in machine learning engineering, generative AI, and natural language processing. I have a strong background in building and deploying large language models, applying advanced ML techniques, and integrating AI solutions into scalable production environments. My expertise includes prompt engineering, AI ethics, model deployment, and real-time analytics. Throughout my career, I have successfully designed and implemented AI systems across diverse sectors such as finance, healthcare, and transportation. I enjoy mentoring teams, collaborating cross-functionally, and leveraging state-of-the-art AI technologies to deliver impactful business outcomes. I am passionate about creating explainable AI and compliance-driven models that drive innovation and efficiency.…I am a Data Scientist and GenAI Engineer with over 10 years of experience specializing in machine learning engineering, generative AI, and natural language processing. I have a strong background in building and deploying large language models, applying advanced ML techniques, and integrating AI solutions into scalable production environments. My expertise includes prompt engineering, AI ethics, model deployment, and real-time analytics. Throughout my career, I have successfully designed and implemented AI systems across diverse sectors such as finance, healthcare, and transportation. I enjoy mentoring teams, collaborating cross-functionally, and leveraging state-of-the-art AI technologies to deliver impactful business outcomes. I am passionate about creating explainable AI and compliance-driven models that drive innovation and efficiency.

Usha Pavani Thopalle

Data Scientist, AI Engineer, AI Developer, +3

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I am a Data Scientist and GenAI Engineer with over 10 years of experience specializing in machine learning engineering, generative AI, and natural language processing. I have a strong background in building and deploying large language models, applying advanced ML techniques, and integrating AI solutions into scalable production environments. My expertise includes prompt engineering, AI ethics, model deployment, and real-time analytics. Throughout my career, I have successfully designed and implemented AI systems across diverse sectors such as finance, healthcare, and transportation. I enjoy mentoring teams, collaborating cross-functionally, and leveraging state-of-the-art AI technologies to deliver impactful business outcomes. I am passionate about creating explainable AI and compliance-driven models that drive innovation and efficiency.…I am a Data Scientist and GenAI Engineer with over 10 years of experience specializing in machine learning engineering, generative AI, and natural language processing. I have a strong background in building and deploying large language models, applying advanced ML techniques, and integrating AI solutions into scalable production environments. My expertise includes prompt engineering, AI ethics, model deployment, and real-time analytics. Throughout my career, I have successfully designed and implemented AI systems across diverse sectors such as finance, healthcare, and transportation. I enjoy mentoring teams, collaborating cross-functionally, and leveraging state-of-the-art AI technologies to deliver impactful business outcomes. I am passionate about creating explainable AI and compliance-driven models that drive innovation and efficiency.

Available to hire

I am a Data Scientist and GenAI Engineer with over 10 years of experience specializing in machine learning engineering, generative AI, and natural language processing. I have a strong background in building and deploying large language models, applying advanced ML techniques, and integrating AI solutions into scalable production environments. My expertise includes prompt engineering, AI ethics, model deployment, and real-time analytics.

Throughout my career, I have successfully designed and implemented AI systems across diverse sectors such as finance, healthcare, and transportation. I enjoy mentoring teams, collaborating cross-functionally, and leveraging state-of-the-art AI technologies to deliver impactful business outcomes. I am passionate about creating explainable AI and compliance-driven models that drive innovation and efficiency.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Data Scientist & GenAI Engineer at Samsara

July 1, 2023 - Present

Led the development of a generative AI-powered fleet operations assistant that summarizes telematics, GPS logs, and driver safety reports, delivering structured insights for automated risk scoring and compliance. Built fine-tuned LLMs leveraging T5 and OpenAI function calling for compliance summarization and real-time decision support. Deployed containerized AI models on Kubernetes with CI/CD pipelines for scalable production workloads. Applied deep learning for computer vision tasks such as defect detection and scene understanding in IoT datasets. Developed classification models, topic modeling workflows, and clustering analyses to extract actionable insights from fleet safety and operational data. Mentored junior analysts and developed intelligent document assistants for maintenance and compliance retrieval. Established automated data pipelines and monitoring systems ensuring model reliability, bias detection, and performance optimization across fleet management use cases.

AI/ML Engineer at Verizon

June 30, 2023 - August 26, 2025

Designed and implemented scalable machine learning pipelines automating feature engineering, model training, and batch inference for healthcare claims data. Developed real-time prediction APIs to classify claims enabling low latency processing and eligibility checks. Built model drift detection workflows triggering automated retraining for sustained compliance and accuracy. Leveraged Spark MLlib and OCR to improve data ingestion times and unstructured text extraction from medical documents. Created automated triage and prioritization pipelines reducing claim review time by 20%. Managed clinical NLP models using Google Vertex AI for optimized training and deployed alerting systems to monitor model and pipeline performance. Integrated AWS Textract for provider PDF processing and deployed ensemble forecasting models enhancing operational planning.

ML Engineer at US Bank

March 1, 2018 - August 26, 2025

Engineered churn prediction and fraud detection systems using ensemble models combining gradient boosting and neural networks to improve financial risk scoring. Automated feature selection pipelines with interpretability via SHAP and implemented anomaly detection to identify unusual transaction patterns in real time. Developed explainable AI dashboards supporting compliance and audit activities. Applied time series forecasting for delinquency and reserve allocation optimization. Collaborated on bias testing and AI model governance standards. Built data pipelines using Kafka, Snowflake, and Airflow ensuring timely features delivery for ML workflows. Utilized GANs for synthetic data augmentation to improve classification and reduce bias across financial services applications. Employed Neo4j graph databases for AML and fraud network analysis.

Data Engineer at Fidelity Investments

June 30, 2015 - August 26, 2025

Developed machine learning algorithms primarily in Python and worked extensively with Caffe deep learning framework. Managed data aggregation and manipulation across diverse sources using tools like Power BI and Business Objects. Implemented Agile methodologies for internal application development focused on integration and master data management. Configured AWS cloud infrastructure for scalable data storage and processing. Worked with big data technologies including Spark, Hadoop, HBase, and Kafka to power streaming analytics and ML workflows. Applied data quality validations and designed data models to optimize analytical workloads. Developed QlikView reporting solutions and performed data mining phases ensuring high data quality and actionable insights for business users.

Data Scientist & GenAI Engineer at Samsara

July 1, 2023 - Present

Built a GenAI-powered fleet operations assistant integrating LLMs and vision models for telematics data summarization, compliance checks, and safety incident analysis. Developed automated compliance policy summarizers and internal GenAI copilots using RAG and LangChain frameworks. Deployed containerized ML models on Kubernetes clusters with CI/CD pipelines using MLflow, GitHub Actions, and Terraform on AWS. Mentored junior analysts on unsupervised learning and built explainable classification models to identify high-risk drivers and vehicles, reducing fleet incidents. Engineered large-scale IoT data pipelines in Databricks, performed feature selection and data augmentation to improve model recall, and designed bias detection audits to ensure fair AI recommendations in fleet safety. Integrated monitoring tools to track model drift and GPU usage for reliable production workloads.

AI/ML Engineer at Verizon

June 30, 2023 - August 26, 2025

Developed scalable ML pipelines in Apache Airflow automating feature engineering and batch inference on healthcare claims data. Designed real-time prediction APIs enabling low-latency claims classification and eligibility checks. Implemented model drift detection triggering retraining pipelines for sustained accuracy and compliance. Leveraged Spark MLlib to reduce ETL times by over 40%. Built NER and entity resolution pipelines extracting clinical variables and developed OCR pipelines for scanned medical forms. Delivered healthcare claims volume forecasting using ensemble time-series models and established monitoring dashboards for model performance using Prometheus and Grafana. Integrated AWS Textract for PDF and forms data extraction and managed model experimentation with MLflow and Weights & Biases.

ML Engineer at US Bank

March 1, 2018 - August 26, 2025

Engineered churn prediction systems using XGBoost with SHAP for interpretability and customer segmentation. Built ensemble fraud detection and credit risk scoring models combining tree-based algorithms with neural networks. Developed anomaly detection for real-time transaction monitoring. Designed explainable AI dashboards for risk and compliance teams and applied time series forecasting for delinquency prediction. Created synthetic data pipelines using GANs for model training and deployed scalable data pipelines integrating Kafka, Snowflake, and Airflow for near-real-time data availability. Leveraged Neo4j for anti-money laundering insights and collaborated with compliance on AI governance and bias detection.

Data Engineer at Fidelity Investments

June 30, 2015 - August 26, 2025

Implemented machine learning algorithms and data pipelines using Python, Spark, Scala, Hadoop, and big data technologies to drive analytics and automation. Developed ETL processes, data modeling, and quality validation to ensure integrity of critical data. Built QlikView models integrating various data sources and contributed to Agile projects focusing on application integration and Master Data Management. Created Workday EIB integrations for HR and financial data extraction and enhanced reporting capabilities. Used deep learning frameworks and various databases to optimize data processing and analytics workflows supporting business intelligence and operational improvements.

Data Scientist & GenAI Engineer at Samsara

July 1, 2023 - Present

Built a GenAI-powered fleet operations assistant leveraging LLMs to summarize telematics, GPS data, and safety reports for risk scoring and compliance. Developed automated compliance summarizers, integrated OpenAI Function Calling for enhanced decision support, and created internal copilots using LLM and RAG stacks for real-time guidance. Implemented monitoring frameworks with Databricks, MLflow, and Terraform to ensure reliable deployment at scale. Led multi-agent AI workflows using LangChain and Google ADK, refined image classification models, and fine-tuned LLMs for IoT datasets. Delivered predictive and classification models for driver safety and operational analytics. Conducted bias audits and enabled zero/few-shot learning for continual model adaptation. Mentored junior analysts and served as a customer-facing consultant deploying ML and RAG solutions.

AI/ML Engineer at Verizon

June 30, 2023 - September 5, 2025

Developed scalable ML pipelines with Apache Airflow for healthcare claims data, automating feature engineering and batch inference. Built real-time prediction APIs for claims classification and eligibility checks. Implemented model drift detection and retraining pipelines to maintain performance. Utilized Spark MLlib to process large-scale EHR data, reducing ETL times significantly. Engineered classification and NER pipelines for clinical variables extraction and automated triage workflows, improving efficiency in healthcare operations. Employed forecasting models for claims volume prediction and integrated OCR technologies. Managed experimentation and version control with MLflow and W&B. Collaborated on delivering GenAI copilots aligned with business goals.

ML Engineer at US Bank

March 1, 2018 - September 5, 2025

Engineered churn prediction and fraud detection systems using ensemble models, integrating XGBoost, LightGBM, and neural networks with SHAP-based interpretability. Built anomaly detection pipelines and specialized performance metrics for financial risk modeling ensuring regulatory compliance. Developed explainable AI dashboards for credit and fraud insights. Constructed data pipelines with Kafka, Snowflake, and Airflow for near real-time data delivery. Deployed GANs for synthetic data augmentation and applied time series models for delinquency and reserve forecasting. Collaborated on AI governance and bias testing to align with compliance. Utilized Neo4j for transaction network analysis enhancing AML capabilities.

Data Engineer at Fidelity Investments

June 30, 2015 - September 5, 2025

Developed machine learning algorithms and performed data manipulation with Python and libraries including Pandas, NumPy, and NLTK. Employed deep learning frameworks like Caffe for various ML tasks. Handled large-scale data processing using Spark, Hadoop, and related Big Data technologies. Designed and optimized data models ensuring database efficiency and integrity. Created QlikView data models integrating multiple data sources for analytics. Applied data validation and cleansing techniques, developed classification models, and implemented end-to-end data automation systems. Collaborated cross-functionally for business requirements gathering and supported Agile development processes.

Data Scientist & GenAI Engineer at Samsara

July 1, 2023 - Present

Led the development of a GenAI-powered fleet operations assistant that summarizes telematics, GPS logs, and driver safety reports to automate risk scoring and compliance checks. Created fine-tuned large language models for summarizing extensive compliance policies, and implemented OpenAI function calling for enhanced bot interactions. Deployed scalable containerized AI services on Kubernetes and automated ML pipelines with MLflow, GitHub Actions, and Terraform. Developed vision models using CNN, transfer learning and self-supervised learning for defect detection. Mentored junior analysts on clustering and supervised machine learning techniques. Built classification pipelines leveraging XGBoost and SHAP for interpretable safety insights. Created data pipelines for large-scale IoT data processing and designed geospatial analytics models for risk zone identification. Introduced zero-shot and few-shot learning for adaptability on new scenarios, integrated monitoring tools for model drift a

AI/ML Engineer at Verizon

June 30, 2023 - September 5, 2025

Developed and automated ML pipelines for healthcare claims data using Apache Airflow, enabling efficient feature engineering and training workflows. Designed and deployed real-time prediction APIs with FastAPI and Docker for claims classification and eligibility checks. Implemented automated model drift detection and retraining to maintain reliability and compliance. Leveraged Spark MLlib to optimize large-scale EHR datasets, improving ETL performance significantly. Built anomaly detection pipelines, clinical document classification models aligned to ICD and CPT codes, and named entity recognition pipelines for clinical variable extraction. Integrated OCR solutions using Tesseract, OpenCV, and AWS Textract to digitize medical documents. Utilized ensemble time series forecasting models for claims volume projections to aid operational planning. Established monitoring and alerting with Prometheus and Grafana to maintain NLP model health. Managed experimentation and version control with ML

ML Engineer at US Bank

March 1, 2018 - September 5, 2025

Engineered churn prediction and fraud detection models combining tree-based algorithms and neural networks to improve credit risk scoring and transaction anomaly detection. Deployed interpretable AI dashboards for risk officers using SHAP and Plotly Dash for compliance and audit transparency. Built credit scoring models and integrated time series forecasting for delinquency predictions. Supported AI model governance and bias testing for regulatory adherence. Developed scalable data ingestion pipelines with Kaga, Snowflake, and Airflow, and generated synthetic data with GANs to enhance model performance and reduce bias. Designed and implemented supervised models for insurance claims automation and customer segmentation using clustering techniques. Employed graph databases to enhance anti-money laundering and fraud capabilities.

Data Engineer at Fidelity Investments

June 30, 2015 - September 5, 2025

Performed data manipulation, aggregation, and validation using Python and various tools. Developed machine learning algorithms and integrated data from multiple sources for reporting and analysis. Utilized big data technologies including Spark, Hadoop, HBase, Cassandra, and MongoDB. Applied supervised classification models for predictive analytics tasks. Designed and optimized data models, created QlikView reports, and participated in full data mining lifecycle. Developed Workday EIB integrations for HR and financial data. Ensured data quality and compliance via validation techniques. Collaborated with business analysts and architects for solution design and process improvements.