Currently an Extern @Pfizer
Reentering the workforce with a focus on AI and data extraction, I'm ready to tackle real-world challenges and enhance my professional journey.
I focus on impactful projects utilizing AI technologies, like my work with Pfizer on automated document insights and data extraction.
.jpg)
Pfizer · ✅ 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.
Developed interactive dashboards using Power BI/Tableau to track e-commerce sales performance and real estate pricing trends. Synthesized raw data into actionable KPIs, enabling stakeholders to identify market shifts and conversion bottlenecks at a glance.
Reentering the workforce with a focus on AI and data extraction, I'm ready to tackle real-world challenges and enhance my professional journey.
I'm an experienced professional reentering the workforce after a break, eager to leverage my skills and knowledge in new opportunities. With a Bachelor’s degree and a commitment to continuous learning, I strive to enhance my competitiveness in the job market. My recent externship at Pfizer has allowed me to work on cutting-edge AI projects, further enriching my expertise and portfolio.
Externships
Pfizer Advanced: AI-Powered Document Insights & Data Extraction Externship
Pfizer
Experience
Process Technical Engineer
Samsung Electro-Mechanics Philippines · Jan 2024 – Apr 2025
Education
University of the Philippines – Los Baños
Bachelor of Science in Chemical Engineering (Cum Laude) · Class of 2023
Xaltius Academy — Singapore (Remote)
Data Science and AI Professional Certificate · Class of 2025
McKinsey.org — Forward Program (Core Skills Level)
Class of 2026
DataCamp
Python Data Associate Certificate
Skills
✅ 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 document-intelligence workflows for pharmaceutical PDFs, combining OCR, computer vision, large language models, and retrieval-augmented generation. The work analyzed a sample vendor file, documented OCR and NLP failure modes with specific examples, and produced cleaned dataframes after initial data inspection and correction.
I documented OCR and NLP failure modes observed in a vendor PDF and produced cleaned, corrected dataframes from inspected datasets, naming specific error patterns and fixes.
I analyzed a sample vendor file and described OCR and NLP failure modes: CV struggled with multi-column tables, scientific graphs, and checkboxes; NLP missed domain terms, complex legal logic, and inconsistent date formats. I reported specific error risks and examples.
The module work described initial data inspection with Pandas, identified and corrected inconsistencies (e.g., malformed ZIPs, negative Experience, mixed-format CCAvg), and produced cleaned dataframes ready for analysis.
Developed interactive dashboards using Power BI/Tableau to track e-commerce sales performance and real estate pricing trends. Synthesized raw data into actionable KPIs, enabling stakeholders to identify market shifts and conversion bottlenecks at a glance.
Conducted Exploratory Data Analysis (EDA) on clinical and lifestyle datasets to identify and visualize significant health risk factors; developed a Tuned XGBoost model using Randomized Search and applied advanced preprocessing, feature scaling, and cross-validation to achieve a model AUC of 0.80 and evaluate feature importance.
Performed extensive cleaning and validation on EPA ozone pollution datasets using Python (Pandas & NumPy), executed missing-value treatment, outlier detection, and data type standardization, and developed visualizations to communicate the impact of data quality on pollution trend accuracy.