Pfizer Externship via ExternI am passionate about utilizing data to enhance public health outcomes and improve healthcare systems.
Discover my work in healthcare data analytics and how I aim to leverage data for impactful public health solutions.
Cleaned and validated FAERS adverse event records in SAS, organizing drug, event, outcome, and reporting fields into structured safety datasets for clinical review. Applied CDISC SDTM and ADaM concepts to standardize adverse event variables. Developed TIBCO Spotfire dashboards with SAS-based safety summaries.
Screened 1,000+ studies in Excel using PRISMA-ScR criteria, creating a structured inclusion and exclusion tracker and extracted variables into Excel evidence tables, summarizing findings into publication-ready research outputs.
I am passionate about utilizing data to enhance public health outcomes and improve healthcare systems.
I am a Public Health major from Long Island University with a focus on healthcare data analytics. Currently, I am gaining practical experience through my externship at TruBridge, where I apply my academic knowledge to real-world challenges in healthcare.
Externships
Pfizer Advanced: AI-Powered Document Insights & Data Extraction Externship
In progress
Experience
Healthcare Data Analytics Extern
TruBridge · Apr 2026 - Jun 2026
Clinical Research Coordinator (REACH Fellow)
Sapna NYC · Aug 2025 - Jan 2026
Clinical Research Intern (Public Affairs, Health Policy & Research)
Second Life e.V. · May 2025 - Aug 2025
Clinical Research Assistant (Dental Clinic)
Rhema Prime Dental Clinic · Jan 2024 - Jun 2024
Clinical Research Assistant (Dental Clinical Practice)
GITAM Dental College & Hospital · Dec 2022 - Dec 2023
Education
Long Island University
Master of Public Health
GITAM Dental College & Hospital
Bachelor of Dental Surgery
Skills
Cleaned and validated FAERS adverse event records in SAS, organizing drug, event, outcome, and reporting fields into structured safety datasets for clinical review. Applied CDISC SDTM and ADaM concepts to standardize adverse event variables. Developed TIBCO Spotfire dashboards with SAS-based safety summaries.
Screened 1,000+ studies in Excel using PRISMA-ScR criteria, creating a structured inclusion and exclusion tracker and extracted variables into Excel evidence tables, summarizing findings into publication-ready research outputs.
Analyzed MIDUS clinical variables in IBM SPSS using regression and ANOVA, cleaned and transformed renal health variables in SPSS and Excel, and prepared Excel visuals and Microsoft Office reports from SPSS outputs.
✅ Verified by Extern
Dig into real healthcare data, uncover patterns, and turn numbers into insights that matter. In this externship with TruBridge, a leading publicly traded healthcare solutions provider, you’ll explore how data and AI are used to track infections, improve outcomes, and support smarter decision-making. You’ll work with large public datasets, build interactive dashboards, and practice skills like statistical modeling and trend analysis—perfect for anyone curious about data, healthcare, or how tech is changing both.
During my externship with TruBridge, I analyzed real healthcare data to uncover significant patterns and generate actionable insights. I engaged with large public datasets, developed interactive dashboards, and honed my skills in statistical modeling and trend analysis. This experience deepened my understanding of how data and AI can enhance healthcare outcomes and decision-making processes.
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In this project, I undertook various tasks that allowed me to apply data analytics in a healthcare context. Below are the key activities I completed during my externship.
✅ Verified by Extern · ⏱️ In progress
Prototype AI-powered document intelligence with Pfizer—using OCR, LLMs, and RAG to automate real enterprise PDF workflows and build a standout portfolio project.
The externship prototyped AI-driven document intelligence workflows combining OCR, LLMs, and retrieval-augmented generation. The work surveyed model architectures and integration patterns, mapped end-to-end PDF processing steps, and produced explanatory material outlining how the components interact in a prototype pipeline.
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I produced a technical summary explaining Transformer attention, next-word prediction, and the training and fine-tuning processes behind large LLMs, and how those mechanisms enable coherent model outputs.
The submission summarized how LLMs used Transformer attention and next-word prediction, described training and fine-tuning of billions of parameters, and explained why that produces coherent responses.
