Software Engineer

Hi, I'm Scott.

Software Engineer @ Lyft

M.S. EECS @ UC Berkeley


San Francisco, CA

scott.lee.3898@gmail.com

Resume (PDF)

in/scottjlee98

About Me

I'm Scott, a Bay Area native, tea connoisseur, and turtle enthusiast. Currently, I'm a software engineer at Lyft, returning after completing my M.S. at UC Berkeley. In the past, I've also had the pleasure of working at other amazing companies like Rubrik and Brilliant.

I'm passionate about designing thoughtful solutions to complex problems. My academic and industry interests include artificial intelligence (machine learning, computer vision), business intelligence (marketing technology, business infrastructure, large-scale logistics), and intersecting technology and education. I fill my free hours by sipping tea, enjoying unique video games, climbing rocks, and trying new restaurants.

Education & Skills

Education
University of California, Berkeley 🐻

M.S. EECS (2020)
B.A. Computer Science (2019)

Teaching

Head TA for Data 8, Data 100, PH 196, PH 142

Skills

Python & Libraries: PyTorch, TensorFlow, scikit-learn, Pandas
Other Languages: SQL, Go, Java, R
Frameworks & Specializations: Airflow, AWS, Mode, Google & Facebook Marketing Tech

Coursework

Computer Vision
Machine Learning
AI in Natural Language Processing
AI in Robotics
AI in Healthcare & Medicine
Algorithms & Complexity
Probability & Random Processes
Convex Optimization
Theoretical Statistics
Linear Modeling
Financial Engineering

Experience

Lyft (2020 - Present)

Software Engineer (Growth Platforms)

Overhauled key component in existing infrastructure for automated driver acquisition, efficiently scaling marketing spend from a state of COVID-shutdown to $1 million weekly spend across three paid media channels.
Led multiple projects directly impacting key team OKRs, partnering with numerous other engineers and scientists in order to boost growth marketers’ productivity; drove both short-term strategy as well as long-term team roadmapping.

RISELab (2018 - 2020)

Graduate Researcher

• Computer Vision (Explainability, Few-Shot)
• Medical Imaging (EKG)

Lyft (2019)

Software Engineering Intern (Marketplace)

• Dual project between infrastructure (generalized pricing API) and modeling (new surge pricing model).
• Conducted extensive data analysis and feature engineering, created dynamic endpoints to fetch features, and owned several pricing experiments.

Rubrik (2018)

Software Engineering Intern (Office 365 Backup)

• Designed and implemented an integral component of the first product launch of Office 365 Backup (Rubrik’s first SaaS product): a robust cloud database and datastore system flexibly compatible with AWS, Azure, and GCP.

Projects

Fido

A Slackbot packed with features to assist teaching staff members, including roster lookup, Piazza paging, and groupshouts.

BerkeleyTime

An augmented course catalog used by over 30,000 UC Berkeley students that provides data on courses, enrollment trends, grade distributions, and more.

Neural-Backed Decision Trees

Improving explainability for deep learning image classification using a decision tree-based structure.


Object-Focused Edge Detection

A general method for altering algorithms for edge detection in order to produce edge mappings that focus on one or few individual objects in an image.

Contact Me

I'm currently located in San Francisco, CA. If you want to grab a cup of tea or reach me otherwise, email is the preferred method. Thanks!