Ken Lau

Business Intelligence Engineer - Amazon
(March 2022 - Present)

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.