Available to hire
I’m an AI/ML Developer with 3+ years of hands-on experience building end-to-end ML and deep learning solutions for healthcare and business domains. I design scalable data pipelines, craft robust models, and collaborate with clinical, finance, and product teams to translate complex data into actionable insights.
I’m proficient in Python, SQL, and cloud-based ML platforms, and I enjoy turning messy data into production-ready AI solutions, with a focus on deployment, monitoring, and data storytelling through dashboards and visualization tools like Tableau and Power BI.
Skills
Language
English
Fluent
Work Experience
AI/ML Developer at Tungsten Automation (United States)
May 1, 2025 - PresentBuilt and deployed predictive ML models (Patient Churn, Retention, Healthcare Utilization) using Python, Scikit-learn, and TensorFlow, achieving 85% accuracy. Engineered features and conducted hyperparameter optimization to improve model performance and generalization. Implemented time-series forecasting techniques for predicting patient outcomes and resource allocation. Designed and deployed production-ready APIs using Flask/FastAPI, enabling real-time integration with healthcare systems. Utilized MLflow for experiment tracking, reproducibility, and deployment pipelines, ensuring scalable AI workflows. Collaborated with finance, clinical, and marketing teams to deliver AI-powered insights that improved patient engagement and reduced churn.
Data Engineer at Codal
July 31, 2023 - October 14, 2025Designed and deployed machine learning models (Regression, Classification, Clustering, XGBoost) for forecasting, classification, and decision-support systems. Automated ETL pipelines and data preprocessing workflows in Python, reducing manual data preparation time. Conducted Exploratory Data Analysis (EDA) and applied statistical techniques to extract insights from large-scale operational and sales data. Performed model validation with Cross-validation, ROC-AUC, Accuracy, Precision, Recall, ensuring production-grade model reliability. Partnered with cross-functional stakeholders to translate business needs into AI-driven automation and optimization solutions, improving operational efficiency.
AI&ML Developer at Tungsten Automation
May 1, 2025 - November 6, 2025Built and deployed predictive ML models (Patient Churn, Retention, Healthcare Utilization) using Python, Scikit-learn, and TensorFlow, achieving 85% accuracy. Engineered features and performed hyperparameter optimization to improve performance and generalization. Implemented time-series forecasting techniques for predicting patient outcomes and resource allocation. Designed and deployed production-ready APIs using Flask/FastAPI for real-time integration with healthcare systems. Used MLflow for experiment tracking and deployment pipelines to ensure scalable AI workflows. Collaborated with finance, clinical, and marketing teams to deliver AI-powered insights that improved patient engagement and reduced churn.
Data Engineer at Codal
July 1, 2023 - July 1, 2023Designed and deployed machine learning models (Regression, Classification, Clustering, XGBoost) for forecasting, classification, and decision-support systems. Automated ETL pipelines and data preprocessing workflows in Python, reducing manual data preparation time. Conducted EDA and applied statistical techniques to extract insights from large-scale operational and sales data. Performed model validation with cross-validation, ROC-AUC, accuracy, precision, recall, ensuring production-grade model reliability. Partnered with cross-functional stakeholders to translate business needs into AI-driven automation and optimization solutions, improving operational efficiency.
AI/ML Developer at Tungsten Automation
May 1, 2025 - PresentBuilt and deployed predictive ML models (Patient Churn, Retention, Healthcare Utilization) using Python, Scikit-learn, and TensorFlow, achieving 85% accuracy. Engineered features and conducted hyperparameter optimization to improve model performance and generalization. Implemented time-series forecasting to predict patient outcomes and optimize resource allocation. Designed and deployed production-ready APIs using Flask/FastAPI for real-time integration with healthcare systems. Utilized MLflow for experiment tracking, reproducibility, and deployment pipelines, ensuring scalable AI workflows. Collaborated with finance, clinical, and marketing teams to deliver AI-powered insights that improved patient engagement and reduced churn.
Data Engineer at Codal
January 1, 2021 - July 1, 2023Designed and deployed machine learning models (Regression, Classification, Clustering, XGBoost) for forecasting, classification, and decision-support systems. Automated ETL pipelines and data preprocessing workflows in Python, reducing manual data preparation time. Conducted Exploratory Data Analysis (EDA) and applied statistical techniques to extract insights from large-scale operational and sales data. Performed model validation with Cross-validation, ROC-AUC, Accuracy, Precision, Recall, ensuring production-grade model reliability. Partnered with cross-functional stakeholders to translate business needs into AI-driven automation and optimization solutions, improving operational efficiency.
Education
Master’s in Computer Science at University of Central Missouri
January 11, 2030 - October 14, 2025Bachelor of Technology in Computer Science Engineering at Institute of Aeronautical Engineering
January 11, 2030 - October 14, 2025Master's in Computer Science at University of Central Missouri
January 11, 2030 - November 6, 2025Bachelor of Technology in Computer Science Engineering at Institute of Aeronautical Engineering Hyderabad, IND
January 11, 2030 - November 6, 2025Master’s in Computer Science at University of Central Missouri
January 11, 2030 - March 5, 2026Bachelor of Technology in Computer Science Engineering at Institute of Aeronautical Engineering
January 11, 2030 - March 5, 2026Qualifications
Industry Experience
Healthcare, Software & Internet, Professional Services
Skills
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