/* I blend technical expertise with a focus on impactful data solutions, driven to enhance my skills and career in AI and data science. */
🟢 Open to work
Currently an Extern @PfizerExplore my portfolio showcasing diverse projects in machine learning, data visualization, and predictive analytics that drive real-world impact.
Created a hybrid stacked model with Scikit-learn and XGBoost to predict 3 factors of long-term financial stability and presented actionable strategies to improve financial stability, specifically lowering debt.
Developed a predictive model with Python to forecast TTC subway delays to present 3 actionable recommendations to several stakeholders on strategies to improve handling TTC delays.
Developed a stock price prediction linear regression model to derive 6 trading and hedging strategies. Ranked top 5 out of several teams for effective hedging strategies and predictions.
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Prototype AI-powered document intelligence with Pfizer—using OCR, LLMs, and RAG to automate real enterprise PDF workflows and build a standout portfolio project.
I blend technical expertise with a focus on impactful data solutions, driven to enhance my skills and career in AI and data science.
I'm Julia Tan, a junior pursuing a Bachelor's in Actuarial Science at the University of Toronto. I served as a Technical/Operations Lead at Riipen Labs, with experience as an Artificial Intelligence Researcher at Algoverse. I'm passionate about harnessing data to drive decisions and improve systems.
Externships
Pfizer Advanced: AI-Powered Document Insights & Data Extraction Externship
Pfizer
Experience
Technical/Operations Lead
Riipen Labs · Mar 2026 - Apr 2026
Artificial Intelligence Researcher
Algoverse · Jun 2025 - Jan 2026
Education
University of Toronto
B.Sc. Actuarial Science and Economics · Class of 2028
Skills
SDSS Datathon · Mar 2026
Created a hybrid stacked model with Scikit-learn and XGBoost to predict 3 factors of long-term financial stability and presented actionable strategies to improve financial stability, specifically lowering debt.
Created a hybrid stacked model with Scikit-learn and XGBoost to predict 3 factors of long-term financial stability and presented actionable strategies to improve financial stability, specifically lowering debt.
SDSS Datathon · Feb 2025
Developed a predictive model with Python to forecast TTC subway delays to present 3 actionable recommendations to several stakeholders on strategies to improve handling TTC delays.
Developed a predictive model with Python to forecast TTC subway delays to present 3 actionable recommendations to several stakeholders on strategies to improve handling TTC delays.
Quantitative Finance Club · Jan 2025
Developed a stock price prediction linear regression model to derive 6 trading and hedging strategies. Ranked top 5 out of several teams for effective hedging strategies and predictions.
Developed a stock price prediction linear regression model to derive 6 trading and hedging strategies. Ranked top 5 out of several teams for effective hedging strategies and predictions.
✅ 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-powered document intelligence workflows for enterprise PDFs. The work combined OCR, large language models, and retrieval-augmented generation to process and extract information from documents. Deliverables included research, architectural notes, and proof-of-concept extraction pipelines.
I produced a technical summary that explained tokenization, embedding formation, next-token prediction mechanics, weight updates during training, and how models select the highest-probability output token.
The submission summarized how LLMs tokenized input, converted tokens to numeric embeddings, learned word relationships by next-token prediction during training, adjusted weights from errors, and produced the highest-probability token as output.