Hi, I’m Veditha Yechuri, a Machine Learning Engineer with 4+ years of hands-on experience delivering production-grade AI solutions across healthcare, payer, provider, and revenue cycle domains in India and the United States. I specialize in clinical NLP, risk stratification, and predictive analytics, building scalable ML systems on AWS and Azure with a strong focus on explainability, bias monitoring, and regulatory compliance. I enjoy collaborating with clinicians and SMEs to translate medical policies into practical AI that improves workflows, reduces costs, and fosters trust in automated decisions. I’m passionate about end-to-end ML lifecycle practices, from data engineering and model deployment to monitoring and governance, ensuring that healthcare AI is safe, auditable, and impactful.

Veditha Yechuri

Hi, I’m Veditha Yechuri, a Machine Learning Engineer with 4+ years of hands-on experience delivering production-grade AI solutions across healthcare, payer, provider, and revenue cycle domains in India and the United States. I specialize in clinical NLP, risk stratification, and predictive analytics, building scalable ML systems on AWS and Azure with a strong focus on explainability, bias monitoring, and regulatory compliance. I enjoy collaborating with clinicians and SMEs to translate medical policies into practical AI that improves workflows, reduces costs, and fosters trust in automated decisions. I’m passionate about end-to-end ML lifecycle practices, from data engineering and model deployment to monitoring and governance, ensuring that healthcare AI is safe, auditable, and impactful.

Available to hire

Hi, I’m Veditha Yechuri, a Machine Learning Engineer with 4+ years of hands-on experience delivering production-grade AI solutions across healthcare, payer, provider, and revenue cycle domains in India and the United States. I specialize in clinical NLP, risk stratification, and predictive analytics, building scalable ML systems on AWS and Azure with a strong focus on explainability, bias monitoring, and regulatory compliance.

I enjoy collaborating with clinicians and SMEs to translate medical policies into practical AI that improves workflows, reduces costs, and fosters trust in automated decisions. I’m passionate about end-to-end ML lifecycle practices, from data engineering and model deployment to monitoring and governance, ensuring that healthcare AI is safe, auditable, and impactful.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

Machine Learning Engineer at CitiusTech, USA
January 1, 2015 - Present
Led AI-driven prior authorization automation using ClinicalBERT and FHIR integration, reducing manual reviews by 40%, accelerating turnaround times by 30%, and saving $4.5M annually. Architected scalable NLP pipelines on AWS SageMaker with MLflow and SHAP explainability to ensure audit-ready clinical decisions while meeting payer compliance and regulatory requirements. Owned end-to-end deployment of healthcare ML models, collaborating with clinicians and SMEs to align predictions with medical policies, improving approval accuracy and provider satisfaction.
Machine Learning Engineer at Hexaware Technologies, India
December 1, 2021 - July 1, 2023
Led hospital bed utilization optimization using time-series forecasting and XGBoost, improving occupancy efficiency by 18% and reducing emergency wait times by 22%. Designed ML pipelines on Azure ML integrating admission, discharge, and transfer data, enabling hospital operations teams to make data-driven capacity planning decisions. Deployed predictive dashboards in Power BI for real-time patient-flow monitoring and built claims denial prediction models reducing denial rates by 25%. Automated pre-submission claim risk classification, decreasing manual rework by 30% and increasing RCM margins. Developed NLP-based clinical document classification pipelines using spaCy and scikit-learn, reducing indexing effort by 60%. Supported batch deployment of document classification services using Flask and Python for scalable digitization and audits. Built pharmacy demand forecasting models using ARIMA and Prophet, reducing stock-outs by 20% and lowering excess inventory costs by 15%. Created anal
Machine Learning Engineer at Encode Testers, India
June 1, 2020 - November 1, 2021
Built machine learning models to classify diagnostic lab reports using OCR and TF-IDF features, reducing manual tagging effort by 55% and improving report retrieval efficiency. Processed scanned medical reports using Tesseract OCR and Python pipelines, enabling structured text extraction that supported downstream classification and compliance audits. Trained and evaluated Logistic Regression and SVM models on labeled healthcare datasets, achieving reliable multi-class accuracy. Analyzed historical OPD appointment data to identify no-show patterns, supporting predictive modeling that reduced missed appointments by up to 15% through targeted interventions. Generated analytical reports and model performance metrics to aid stakeholders in interpreting predictions and implementing reminder actions.

Education

Masters in Data Science at University of Maryland Baltimore County, MD
August 1, 2023 - May 1, 2025

Qualifications

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Industry Experience

Healthcare, Professional Services, Software & Internet