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Driving Strategic Excellence & Innovation
Experienced Information Technology professional with a strong background in data analysis, machine learning, and web development. Skilled in Python, JavaScript, data visualization, and database management. Demonstrated expertise in developing machine learning models and implementing data-driven applications.
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Collected, cleaned, and analyzed large datasets to identify patterns and improve data accuracy and reporting efficiency.
Developed interactive dashboards and visual analytics in Power BI and Tableau to support organizational decision-making.
Automated data workflows and validation processes using Alteryx, reducing manual reporting time by 25%.
Managed purchase and budget records through Workday, ensuring compliance and data consistency across departments.
Taught undergraduate courses in Python Programming, Data Structures and Algorithms, and Machine Learning.
Designed and delivered hands-on coding labs and projects integrating real-world datasets and problem-solving techniques.
Guided students in developing data-driven applications and implementing machine learning models using Python libraries such as Pandas, NumPy, and Scikit-Learn.
Mentored student research in statistical modeling and neural network design.
Analyzed and modeled Electric-Field datasets using advanced Machine Learning and Neural Network techniques to identify operational inefficiencies and improve predictive accuracy.
Cleaned, transformed, and validated data using Python (Pandas, NumPy) and SQL, ensuring data integrity and optimizing analysis pipelines.
Developed RESTful APIs in Django to automate data processing and integrated Java-based modules to enhance system interoperability and performance.
Designed interactive dashboards in Plotly to visualize key metrics, enabling stakeholders to make data-driven decisions.
Developed a Python-based email validation system to verify domain authenticity and detect blacklist entries, improving data reliability and system security.
Implemented the SMTP protocol and integrated machine learning algorithms to enhance validation accuracy and scalability.
Automated data cleaning and verification pipelines, reducing manual review time by 30%.
Analyzed current research on Digital Twin technology in healthcare, focusing on applications for patient monitoring, predictive analysis, and treatment optimization.
Conducted research on predicting diabetes based on patient symptoms without requiring invasive laboratory tests. Applied Machine Learning and Neural Network models to analyze symptom datasets and identify high-risk individuals. Developed a predictive framework that can assist healthcare providers in early detection and preventative care.
Conducted research on predicting breast cancer using machine learning, aiming to enable early detection and improve patient survival rates. Analyzed patient datasets using ML algorithms to identify critical patterns and high-risk indicators. Developed a predictive model to assist healthcare professionals in diagnosis and timely intervention.
Arizona State University
GPA: 4/4
ITM(SLS)Baroda University
GPA: 8.30/9
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Transform your organization with proven leadership expertise and strategic vision.