Aiden Wan

Hi there—thanks for dropping in.

I'm Aiden Wan, currently a data science graduate student at UCI.

and what you're seeing is my data stories pressed to vinyl.

Put the record on and follow the grooves;

each track shows how I turn raw data into insights you can feel.

Let's spin!

Tracklist

[Side A: internships]

Side A is the radio cut: internship singles where I learned to turn messy numbers into clear business wins. You can find all the full details in my resume!

1.
eBay Data Science, Business Development
Mar 2024 – Aug 2024

My latest internship, where I worked across user segmentation, causal inference, ETL pipeline development, and predictive modeling — helping the team uncover insights, streamline data, and make smarter decisions.

2.
Rednote Strategy Product Manager, Governance
Jul 2023 – Jan 2024

Probably my favorite experience — I built strategies and models for content moderation, helping shape a sincere, welcoming, and safe community for users.

3.
ByteDance Data Science, E-commerce
Dec 2022 – Jun 2023

My very first internship. I designed A/B tests, built visualization dashboards, and applied machine learning to e-commerce data, helping drive new feature launches and fuel revenue growth.

[Side B: original projects]

Flip to Side B for the unreleased B-sides — passion projects you've probably never seen before!

4.
Postcard of Us Automated Daily Memory Emails

For my best friend's birthday, I built a time machine: every morning in 2025, they receive a personalized "on-this-day" email, recapping everything we texted on that date over the past four years.

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Postcard of Us
Film Electrocardiogram
5. Film Electrocardiogram Visualize a movie's emotional arc

Film Emotion Analyzer turns any subtitle file into an interactive emotional arc: it scores each line with transformer embeddings, applies Gaussian smoothing per act, and adds hover tooltips for key moments—transforming raw dialogue into a cinematic journey.

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[Side C: other projects]

Need one more spin? Side C holds the remixes and collabs like kaggle competitions.

6. Recommender System Candidate generation & re-ranking

This collaborative Kaggle project builds a two-stage recommender for OTTO: session co-visitation for candidate generation, followed by XGBoost reranking on temporal, behavioral, and popularity features—predicting the most likely items for clicks, cart additions, and purchases.

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Recommender System

About Me

Aiden Wan

I'm Aiden Wansomeone who loves working with data, and building systems where precision meets emotion.

This portfolio is inspired by BRAT, my favorite album of 2024 — an album where delicate, vulnerable lyrics live inside sharp, technical dance production. I loved how something so mechanical could still carry so much feeling — and it made me think: why can't data do the same?

Every experience here follows that idea: balancing technical depth with human resonance. Whether it's my internships or the gift I built for a friend, each project aims to connect — not just operate.

Outside of data, I'm a music and film lover. I believe storytelling — whether through sound, image, or system design — is what truly brings people together.

Thanks for stopping by!