
Elizabeth Lee
Engineering / Architecture
About Elizabeth Lee:
Highly accurate and experienced Software Engineer/Data Scientist adept at collecting, analyzing, and interpreting large datasets, developing new forecasting models, and performing data management tasks. A result-oriented professional with over 8 years’ experience in software development and enhancement, service delivery and relationship management within the technology domain.
Skills: Pyspark, Python(Pandas, Pytorch, Numpy, Scipy, Seaborn, Matplotlib, Plotly, Keras, Tensorflow), SAS, Java, Git, MySQL, Oracle
Exposure: JavaScript, R, Scala, PostgreSQL, SQLite, C#, html5, CSS
Experience
Data Scientist
Feb 2019 - Present · 4 yrs 1 moFeb 2019 - Present · 4 yrs 1 mo
● Built an automatic defect detection tool based on statistical analysis and predictive data modeling such as Gradient Boosting using Python saving $11M annually.
● Implemented several dashboard visualization applications to help customers to improve the manufacturing process using Python language, Dash, and Streamlit framework, leading to hundreds of new users.
● Automated all data visualization reports of existing machine learning programs using python saved approximately 50 hours of generating reports.
Software Engineer
Nov 2017 - Feb 2019 · 1 yr 4 mosNov 2017 - Feb 2019 · 1 yr 4 mos
● Created dozens of new features of the web-based Manufacturing Operating System using Java, improving UX.
● Fixed bugs from the existing web-based system and implemented enhancements improving web functionality and speed by 20%.
● Created and improved documentation to help business users understand the system more easily saving about 10 hours weekly of troubleshooting guiding end-users.
Education
BA in Statistics, University of California, Berkeley Graduated in June 2015
MS in Computer Science, Arizona State University Graduated in Feb 2023
Relevant Courses: Software Security, Artificial Intelligence, Software Verification and Validation ,Mobile Computing, Advanced Software Analysis and Design, Data Processing at Scale, Statistical Machine Learning, Data Mining, Data Structure and Algorithms, Structure, and Interpretation of Computer Programs, Reproducible and Collaborative Data Science, Computing Data, Modern Statistical Prediction and Machine Learning
PROJECT WORK
Hand Gesture Recognition for Smart Home 2020
- Developed a python program that identifies videos of hand gestures for smart home application using CNN(convolutional neural network) resulted saving hundreds of hours of manual classification.
NYC Hot Spot Analysis 2020
- Developed a program that identifies statistically significant spatial hot spots in New York City using Yellow Cab taxi trip records using Scala and Apache Spark saving thousands of hours of finding the hot spots manually.
Handwritten digits classification 2020
- Developed a program that classifies images of handwritten digits using CNN and naive bayes algorithm in Python saving hundreds of hours of manual classification.
Spam Filtering 2014
- Developed a Spam Filtering program that classifies whether an email is a spam or non-spam using Random Forest in Python resulting in above 98% accuracy and saving hours of time to filter spam emails and protecting from scams.
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