A data enthusiast intrigued to turn data analytics into valuable insights and help businesses grow.
An analytic thinker who can code with SQL, Python, and R.
Able to build datasets and pipelines for ETL, visualization, and reporting.
Familiar with statistical and machine learning models for data analysis and prediction.
Comfortable with working with cross-functional teams. Always willing to teach and learn from others.
Along my path in the data field, I have worked on projects on ...
Projects: Indoor 3-D Positioning of Wireless Communication Base Stations, Revenue Prediction by Shipping Analysis
Projects: Stock Price Prediction in Big Recessions, Box Office Revenue Prediction, Forest Fire Detection
Projects: Daily News Headlines
Projects: Squirrel Reporting Web App
Predict the actual delivery time of products manufactured in different countries and shipped in different methods
Calculate revenues in next three months according to predicted delivery dates
Delivered this model to finance team and controlled its error under 15%
Identified recession periods in the past two decades.
Transformed classy trading rules into techinical language.
Built a Random Forest model in a time-series manner.
Improved the 3-day prediction accuracy by 9%
Scraped headline news from famous News Websites
Classified news into 10 topics
Saved one hour's reading time for the internal consultant team
Analyzed public economic data from the Canadian government
Identified structural breaks of small business growth in the British Columbia area
Figured out the general relationship between the Olympics games and small business growth
Built a web app to allow users to report squirrel sightings in the central park area
Users could also check real-time squirrel sighting distribution from our website
Interesting web app with user-friendly interfaces
Scraped the data of over 30,000 movies from TMDB websites
Explored the relationship between movies features and its box office revenue
Combined internal movie features with external economical indicators to increase prediction accuracy by 5%
Proposed a linear regression model between measurement coordinates and actual coordinates of mobile terminals that achieved an error of less than 1 meter
Reduced the number of necessary base stations from 30 to 3
Extract 15 image features from satellite pictures
Identified forest fire by analyzing image color, brightness and smoke texture
Achieved a prediction accuracy of 91.2%
It took a long journey for me to find my passion for data science. If you are interested in the fields that I have explored, I will be more than happy to tell you my story!
I am the designer of two high-speed communication chips and the owner of an IEEE conference paper.
I used to be the main designer of a 600,000-yuan research project.
I used to be the winner of an IT Entrepreneurship Competition and given a 200,000-yuan venture fund.
I used to work for two famous securities companies in China and won 2nd place among 568 teams in a national investment research competition.