Currently an Extern @TruBridge
I’m a graduate student passionate about transforming data into actionable insights. Ready to make an impact in the world of data science!
Explore my hands-on projects, including real-world data analytics in healthcare, showcasing my skills in data interpretation and visualization.
.jpeg)
TruBridge · ✅ Verified by Extern · ⏱️ In progress
A TruBridge externship in healthcare data analytics focused on working with large public datasets, statistical modeling, trend analysis, and dashboard-ready deliverables.
Optimized an end-to-end retail ETL pipeline, achieving a 35% cost allocation margin by processing and cleaning transactional datasets. Tracked a 62.30% profit margin and a $222.50 median sales threshold, isolating a 190.93% transaction surge in the UAE ($680.79); published interactive desktop/mobile dashboards to Power BI Service with automated revenue alerts.
I’m a graduate student passionate about transforming data into actionable insights. Ready to make an impact in the world of data science!
I am a graduate student at the University of Texas Arlington pursuing a Master's Degree in Data Science. My journey is just beginning as I aim to gain confidence and experience in the real-world work environment.
Externships
TruBridge Healthcare Data Analytics Externship
TruBridge
Experience
Associate
Compass Group · January 2026 - May 2026
Customer Success Intern
Orient IT Services · May 2024 - August 2024
Market Research Analyst Intern
Bahwan CyberTek · December 2022 - January 2023
Healthcare Analytics Extern
TruBridge · May 2026
Education
The University of Texas at Arlington
Master of Science in Data Science | GPA: 3.667/4.0 · Class of 2027
Delhi Technological University
Bachelor of Technology in Computer Engineering | CGPA: 7.44/10 · Class of 2025
Skills
✅ Verified by Extern · ⏱️ In progress
A TruBridge externship in healthcare data analytics focused on working with large public datasets, statistical modeling, trend analysis, and dashboard-ready deliverables.
The externship analyzed public healthcare datasets to investigate links between employment status and mental health and to study hospital readmission drivers. Work combined a selected Kaggle mental-health survey with merged CMS hospital records, producing a cleaned dataset of 11,699 rows, five EDA visualizations, and a documented research report with data provenance. Analyses included correlation
I produced a cleaned, quality-checked dataset of 11,699 hospital-condition records, selected a Kaggle mental-health survey for the research question, generated five EDA charts, ran correlation tests, regression and ANOVA, and compiled a documented research report with dataset links and rationale.
I defined a focused research question about employment status and mental health, listed search terms and data sources, evaluated multiple datasets, and selected a Kaggle mental health survey as the most suitable dataset for analysis. I documented dataset links and rationale.
I selected CMS hospital datasets, inspected variables, removed duplicates, handled missing values, standardized formats, created derived age groups, applied normalization, and produced a cleaned, quality-checked dataset of 11,699 rows ready for EDA.
The project analyzed merged CMS datasets to explore how ownership, rating, emergency services, and discharge volume related to readmission measures. I cleaned 11,699 records, produced five charts (histogram, scatter, bar, scatter with regression, boxplot), and reported findings on correlations and…
The project merged two CMS datasets, cleaned and validated ~11,699 hospital-condition records, ran EDA, correlation tests, regression and ANOVA, and produced visualizations. Findings showed higher hospital quality ratings aligned with lower excess readmission ratios.
Optimized an end-to-end retail ETL pipeline, achieving a 35% cost allocation margin by processing and cleaning transactional datasets. Tracked a 62.30% profit margin and a $222.50 median sales threshold, isolating a 190.93% transaction surge in the UAE ($680.79); published interactive desktop/mobile dashboards to Power BI Service with automated revenue alerts.
Built a T-SQL pipeline to clean and segment minute-level tracking data over a 31-day window, engineering a custom sleep hygiene metric to isolate rest patterns. Designed a dual-dashboard suite uncovering a 325% active-to-sedentary gap and a Sunday slump (820 vs. 1,207 steps), delivering a roadmap for targeted haptic alerts.
Engineered 10+ visualizations and performed comprehensive EDA, revealing trends and relationships between temperatures and precipitation.
Developed an image forgery detection model with Generative Adversarial Networks (GAN)-based augmentation; improved detection accuracy by 1.5% on evaluation data.