• Optimized clinical outcomes across 5 key service lines (Cardiology, Oncology, Orthopedics, Neurology, and Emergency Medicine) at 15 HCA Healthcare facilities.• Leveraged advanced SQL queries in Teradata and Google Cloud Platform to extract and model data from 20+ disparate databases, processing over 1.5 million patient records daily.• Developed a comprehensive data pipeline using Python, automating 80% of data extraction, cleaning, and preprocessing tasks, reducing manual effort by 40… Show more • Optimized clinical outcomes across 5 key service lines (Cardiology, Oncology, Orthopedics, Neurology, and Emergency Medicine) at 15 HCA Healthcare facilities.• Leveraged advanced SQL queries in Teradata and Google Cloud Platform to extract and model data from 20+ disparate databases, processing over 1.5 million patient records daily.• Developed a comprehensive data pipeline using Python, automating 80% of data extraction, cleaning, and preprocessing tasks, reducing manual effort by 40 hours per week. Aggregated and analyzed data from internal HCA Healthcare systems and external sources (CMS, NHSN, and specialty-specific registries), creating a holistic view of performance benchmarks.• Created a suite of 10 interactive Tableau dashboards and 5 Power BI reports, reducing report generation time from 5 days to 6 hours and improving real-time decision-making for clinical leadership.• Conducted in-depth statistical analysis using R, identifying factors contributing to a 12% reduction in 30-day readmission rates across participating facilities.• Developed a machine learning model using Python and scikit-learn to predict patient length of stay, achieving 85% accuracy and enabling more efficient resource allocation. Show less

• Utilized SQL queries to extract and analyze data from PeopleSoft HR and Financial modules for various projects.• Developed and maintained PS Queries to generate custom reports and extract data from PeopleSoft databases.• Played a key role as an intern in the integration process between UT System's ERP systems and BenefitFocus, a benefits administration vendor.• Facilitated the transfer of employee, dependent, and retiree data for over 300,000 staff and a million students across… Show more • Utilized SQL queries to extract and analyze data from PeopleSoft HR and Financial modules for various projects.• Developed and maintained PS Queries to generate custom reports and extract data from PeopleSoft databases.• Played a key role as an intern in the integration process between UT System's ERP systems and BenefitFocus, a benefits administration vendor.• Facilitated the transfer of employee, dependent, and retiree data for over 300,000 staff and a million students across Texas. Responsible for mapping data elements from ERP systems to the vendor's system for both inbound and outbound interfaces.• Collaborated with cross-functional teams to identify and address data discrepancies and errors, contributing to seamless data transmission and processing. Show less

• Supported graduate students in Business Data Warehousing and Organization for Business Analytics, offering guidance on data management and ETL processes.• Conducted over 10 workshops on SAP Analytics for data visualization and enterprise reporting, enabling students to build professional-level dashboards.• Delivered hands-on training sessions in Microsoft Azure for data storage and analytics, enhancing student proficiency with cloud-based data solutions.• Developed course… Show more • Supported graduate students in Business Data Warehousing and Organization for Business Analytics, offering guidance on data management and ETL processes.• Conducted over 10 workshops on SAP Analytics for data visualization and enterprise reporting, enabling students to build professional-level dashboards.• Delivered hands-on training sessions in Microsoft Azure for data storage and analytics, enhancing student proficiency with cloud-based data solutions.• Developed course materials, including assignments and projects focused on real-world applications of data warehousing and analytics in business contexts.• Provided one-on-one tutoring to help students apply SQL, data modeling, and transformation techniques to solve complex business problems.• Evaluated and provided feedback on over 100 assignments, strengthening students' analytical thinking and technical skills. Show less

• Developed a real-time financial dashboard using Power BI, reducing reporting time by 75% and enabling immediate decision-making for Csuite executives. Designed and maintained a SQL database for real-time transaction monitoring, detecting fraud.• Leveraged pandas and NumPy to process 1M+ daily financial transactions, reducing data preparation time by 60%.• Applied association rule mining to analyze 10M+ customer transactions, uncovering cross-selling opportunities that increased… Show more • Developed a real-time financial dashboard using Power BI, reducing reporting time by 75% and enabling immediate decision-making for Csuite executives. Designed and maintained a SQL database for real-time transaction monitoring, detecting fraud.• Leveraged pandas and NumPy to process 1M+ daily financial transactions, reducing data preparation time by 60%.• Applied association rule mining to analyze 10M+ customer transactions, uncovering cross-selling opportunities that increased revenue.• Utilized machine learning algorithms to analyze high-frequency trading data, identifying profitable patterns that increased daily trading revenue. Created predictive models using Python and scikit-learn to forecast stock prices, resulting in a 12% increase in portfolio performance.• Developed a suite of 20+ financial KPIs, providing real-time performance insights that led to a 10% improvement in operational efficiency.• Designed and executed 25+ A/B tests on user interfaces, improving user engagement by 35% and reducing churn by 20%.• Utilized AWS Lambda to process 500GB+ of financial data daily, achieving a 70% cost reduction compared to on-premise solutions.• Developed 30+ macros and VBA scripts, automating repetitive tasks and saving 100+ man-hours monthly. Show less

• Conducted Exploratory Data Analysis (EDA) and data cleaning processes to prepare the dataset for analysis and visualized using Seaborn for correlation plots to identify influential features affecting household power consumption.• Employed Principal Component Analysis (PCA) to identify and understand the principal components, enhancing model interpretability and applied linear regression using standard train-test split to build a predictive model for power consumption given important… Show more • Conducted Exploratory Data Analysis (EDA) and data cleaning processes to prepare the dataset for analysis and visualized using Seaborn for correlation plots to identify influential features affecting household power consumption.• Employed Principal Component Analysis (PCA) to identify and understand the principal components, enhancing model interpretability and applied linear regression using standard train-test split to build a predictive model for power consumption given important features.• Leveraged IBM Watson Studio for model building, resulting in a 15% reduction in energy consumption prediction errors when using metrics like MSE, MAE. Also developed and deployed a Flask-based web application on IBM Cloud, facilitating end-user access to power consumption insights achieving a 25% performance improvement. Show less