Algobeans is the brainchild of two data science enthusiasts, Annalyn (University of Cambridge) and Kenneth (Stanford University). We noticed that while data science is increasingly used to improve workplace decisions, many people know little about the field. Hence, we created Algobeans so that everyone and anyone can learn – be it an aspiring student or enterprising business professional. Each tutorial covers the important functions and assumptions of a data science technique, without any math or jargon. We also illustrate these techniques with real-world data and examples.
Our posts are our own, and do not represent the views of our past/present employers.
I’m based in the San Francisco Bay Area, working as a data scientist at Amazon Web Services. Previously, I have worked as a statistics tutor at the University of Michigan (Ann Arbor), a research associate for Disney Research’s behavioral sciences team, and also an analyst for the Singapore government, where my analysis was used to make informed decisions on large-scale public policy.
I completed my MPhil in Psychometrics at the University of Cambridge Psychometrics Centre, where I programmed cognitive tests for job recruitment.
I am fluent in English and Mandarin Chinese, and can converse in Japanese – a skill gleaned from hours of watching too much anime. I was also a competitive archer representing Singapore in regional competitions.
I completed my MS in Statistics at Stanford University, and was the top student for all 3 years of my MORSE degree at the University of Warwick (MORSE: Mathematics, Operational Research, Statistics, and Economics).
At University of Warwick, I was a research assistant with the Operational Research & Management Sciences Group working on bi-objective robust optimization with applications in networks subject to random failures.
I am interested in data analytics, and I am constantly honing my skills through reading and practice. From 2015 to 2016, I participated in a series of 4 data-related competitions organized by the Ministry of Defence (Singapore), Monetary Authority of Singapore, Singtel, and ConneXionsAsia, developing machine learning models as well as privacy protection methods, eventually placing podium finishes (top 3) for all of them.
I enjoy traveling and have visited over 20 countries by the age of 23. I hope to use my skills to enhance policy-making in the government and improve the lives of ordinary citizens.
Pssst… We also wrote a book. Numsense! Data Science for the Layman (no math added) has been used by top universities like Stanford and Cambridge as introductory reference text. Download a free PDF sample here, or grab it at just $2.99 on Amazon.