Ming Lee
Engineer/Consultant
Contact Info
- minghanjlee@gmail.com
- CA, USA
- wontonoodle.github.com
Skills
Django, Flask
Python, R
Spark, Airflow
JavaScript
HTML5 & CSS3
SQL
Excel, VBA
About Me
A dedicated professional with a profound fascination for data science and technology, equipped with ten years of experience in the energy sector. Specialized in data collection, analysis, and performance prediction for industrial units. Currently in the final semester of MSDS while serving as a Teaching Assistant for DESIGN PRINCIPLES & CAUSAL INFERENCE, and working as a full-time Process Design Lead. Striving to apply data science principles into the current role to enhance operational efficiency and precision.
Experience
Energy Companies
2013-Present
Senior Process Data Engineer
- Deployed machine learning forecasting models on product yields and catalyst deactivation based on changes in the feed properties and operating conditions.
- Developed dashboards to monitor the production process of a manufacturing plant with KPIs.
- Created and automated Python scripts that collected, pre-processed, and transformed process data into a database that feeds the unit monitoring templates on a monthly basis to forecast and optimize unit performance.
- Responsible for presenting process KPIs and technical recommendations to upper management
-
projects
Current
Tennis Racket Recommender
Constructed an extensive database comprising over 1,000 tennis rackets through web scraping. Developed and trained a ML model achieving over 85% accuracy in predicting racket power levels. Devised a system that generates a curated list of recommended rackets driven by user inputs.
Stack: Python, SQL, Shiny
Education
University of Texas at Austin
2021-2023
M.S. Data Science
Pursuing a comprehensive blend of statistics and computer science at a 50/50 ratio, with the goal of applying this knowledge to address practical, real-world challenges..
ADVANCED PREDICTIVE MODELS
DATA EXPLORATION & VISUALIZATION
DATA STRUCTURES & ALGORITHMS
PROBABILITY & INFERENCE
DESIGN PRINCIPLES & CAUSAL INFERENCE
MACHINE LEARNING
DEEP LEARNING
OPTIMIZATION
REGRESSION & PREDICTIVE MODELING
NATURAL LANGUAGE PROCESSING