/* 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. Constructed 6 Matplotlib visualizations for each factor to identify patterns, and detect outliers, strengthening the model. Presented actionable insights to stakeholders for strategies to improve financial stability, specifically lowering debt.
Developed predictive analyses by building a TensorFlow neural network in Python to forecast TTC subway delays, achieving an MSE of 1.1. Created Matplotlib visualizations to reveal delay patterns, recommending prioritization of transfer station congestion mitigation. Presented 3 actionable recommendations to several stakeholders on strategies to improve handling TTC delays.
Developed a stock price prediction linear regression model with Scikit-learn to derive 6 trading and hedging strategies. Visualized the LSTM, ARIMA, and linear regression predictions against the actual prices with Matplotlib, with linear regression having the closest predictions. Ranked top 5 out of several teams for effective hedging strategies and predictions.
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
Created a hybrid stacked model with Scikit-learn and XGBoost to predict 3 factors of long-term financial stability. Constructed 6 Matplotlib visualizations for each factor to identify patterns, and detect outliers, strengthening the model. Presented actionable insights to stakeholders for 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. Constructed 6 Matplotlib visualizations for each factor to identify patterns, and detect outliers, strengthening the model. Presented actionable insights to stakeholders for strategies to improve financial stability, specifically lowering debt.
Developed predictive analyses by building a TensorFlow neural network in Python to forecast TTC subway delays, achieving an MSE of 1.1. Created Matplotlib visualizations to reveal delay patterns, recommending prioritization of transfer station congestion mitigation. Presented 3 actionable recommendations to several stakeholders on strategies to improve handling TTC delays.
Developed predictive analyses by building a TensorFlow neural network in Python to forecast TTC subway delays, achieving an MSE of 1.1. Created Matplotlib visualizations to reveal delay patterns, recommending prioritization of transfer station congestion mitigation. Presented 3 actionable recommendations to several stakeholders on strategies to improve handling TTC delays.
Developed a stock price prediction linear regression model with Scikit-learn to derive 6 trading and hedging strategies. Visualized the LSTM, ARIMA, and linear regression predictions against the actual prices with Matplotlib, with linear regression having the closest predictions. Ranked top 5 out of several teams for effective hedging strategies and predictions.
Developed a stock price prediction linear regression model with Scikit-learn to derive 6 trading and hedging strategies. Visualized the LSTM, ARIMA, and linear regression predictions against the actual prices with Matplotlib, with linear regression having the closest predictions. Ranked top 5 out of several teams for effective hedging strategies and predictions.