About Me
I have 6+ years of professional experience in data science.
I completed a M.Sc. in Statistics at the University of British Columbia (UBC).
I like to play Ultimate Frisbee.
Academics
Univeristy of British Columbia
Master's in Statistics:
September 2013 to August 2015
Bachelor's in Statistics with Co-op:
September 2008 to May 2013
Nash Medal Recipient
Publication
2016: International Journal of Electronics and Communications Volume 79, Issue 9
Authors: Ken Lau, Matias Salibian-Barrera, Lutz Lampe
Title: Modulation Recognition in the 868 MHz Band Using Classification Trees and Random Forests
Selected Coursework
Statistics & Mathematics
Course | Description |
---|---|
STAT 545/547M | Data Science Tools |
STAT 560/561 | Statistical Theory | STAT 550 | Statistical Consulting |
STAT 547C | Proabability Theory |
STAT 447C | Statistical Machine Learning |
STAT 443 | Time Series |
STAT 404 | Design & Analysis of Experiments |
STAT 306 | Regression |
STAT 344 | Survey Sampling |
MATH 316 | Advanced Calculus |
MATH 307 | Applied Linear Algebra |
MATH 303 | Stochastic Processes |
Computer Science
Course | Description |
---|---|
CPSC 540 | Machine Learning |
CPSC 547 | Information Visualization |
CPSC 546 | Numerical Optimization |
CPSC 404 | Advanced Relational Database |
CPSC 320 | Algorithms and Data Structures |
CPSC 317 | Computer Networking |
CPSC 313 | Hardware and Operating Systems |
CPSC 310 | Software Engineering |
CPSC 302/303 | Scientific Computing |
Other coursework from MOOC:
Coursera:
Udacity:
Work Experience
Business Intelligence Engineer - Amazon
(March 2022 - Present)
reference: amazon.ca
Data Scientist - Hothead Games
(Oct 2017 - Nov 2021)
- Use Python and R to create machine learning and statistical models for predictions and deep-dive analysis on player behavior improving user engagement and retention.
- Use SQL and Tableau to build dashboards to better understand player behavior/progression/economy such as funnels to identify pinch points in the game.
- Develop an A/B test reporting platform for all games, and provide guidance in decision making based on statistical confidence.
- Help game and marketing teams plan the design of experiments to accurately measure feature and campaign performance.
- Implement forecasting models using machine learning to determine the performance, improvement, and profitability of a game.
- Develop a robust model to assess theme test experiments on semi-randomized data.
- Significantly improve the data-driven culture of the company by effectively communicating analytical results across all departments in the company.
- Work on data pipelining projects using tools in AWS and Jenkins to add and modify columns in the main tables used by the analytics team.
Data Scientist - Alberta Gaming and Liquor Commission
(Aug 2015 - Aug 2017)
- Build predictive models using statistics and machine learning to determine the success rate of new games based on different factors such as denomination, game theme, platform, level of bet, etc.
- Analyze and track the impact of various events in Alberta and AGLC including concerts, marketing campaigns, power outages, floor re-organization, etc.
- Process data and build dashboards that monitor success rates for terminal add-ons at all sites across Alberta.
- Deep dive analysis on progressive games (slots with jackpots), supply/demand of game play at the casino-level, and impact of different locations on casino floor.
- Consistently collaborate and communicate with product specialists and managers to improve business processes.
Research Assistant - UBC (Jan 2014 - Feb 2015)
- Simulate transmission signals in Matlab.
- Implement new feature variables for tree-based classifiers using R.
- Improve predictive performance of existing methods.
Data Analyst Intern - Environment Canada (Feb 2013 - Aug 2013)
- Predict air quality in ozone, nitrate, and particle mass elements.
- Implement and optimize boosting trees and support vector machine regressors.
- Impute missing data using nearest neighbor and multiple imputation methods.
Programming Skills
Advanced | Python, R, SQL, C#, Javascript |
Intermediate | Matlab, Java, Hadoop, Spark, Git |