Ask Why! Finding motives, causes, and purpose in data science
Some people equate predictive modelling with data science, thinking that mastering various machine learning techniques is the key that unlocks the mysteries of the field. However, there is much more to...
View ArticleCustomer lifetime value and the proliferation of misinformation on the internet
Suppose you work for a business that has paying customers. You want to know how much money your customers are likely to spend to inform decisions on customer acquisition and retention budgets. You’ve...
View ArticleMy 10-step path to becoming a remote data scientist with Automattic
About two years ago, I read the book The Year without Pants, which describes the author’s experience leading a team at Automattic (the company behind WordPress.com, among other products). Automattic is...
View ArticleAdvice for aspiring data scientists and other FAQs
Aspiring data scientists and other visitors to this site often repeat the same questions. This post is the definitive collection of my answers to such questions (which may evolve over time). How do I...
View ArticleEngineering Data Science at Automattic
Originally posted on Data for Breakfast: Most data scientists have to write code to analyze data or build products. While coding, data scientists act as software engineers. Adopting best practices from...
View ArticleDefining data science in 2018
I got my first data science job in 2012, the year Harvard Business Review announced data scientist to be the sexiest job of the 21st century. Two years later, I published a post on my then-favourite...
View ArticleReflections on remote data science work
It’s been about a year and a half since I joined Automattic as a remote data scientist. This is the longest I’ve been in one position since finishing my PhD in 2012. This is also the first time I’ve...
View ArticleThe most practical causal inference book I’ve read (is still a draft)
I’ve been interested in the area of causal inference in the past few years. In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning....
View ArticleHackers beware: Bootstrap sampling may be harmful
Bootstrap sampling techniques are very appealing, as they don’t require knowing much about statistics and opaque formulas. Instead, all one needs to do is resample the given data many times, and...
View ArticleBootstrapping the right way?
Bootstrapping the right way is a talk I gave earlier this year at the YOW! Data conference in Sydney. You can now watch the video of the talk and have a look through the slides. The content of the talk...
View ArticleA day in the life of a remote data scientist
Earlier this year, I gave a talk titled A Day in the Life of a Remote Data Scientist at the Data Science Sydney meetup. The talk covered similar ground to a post I published on remote data science...
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Software commodities are eating interesting data science work
The passage of time makes wizards of us all. Today, any dullard can make bells ring across the ocean by tapping out phone numbers, cause inanimate toys to march by barking an order, or activate remote...
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Many is not enough: Counting simulations to bootstrap the right way
Previously, I encouraged readers to test different approaches to bootstrapped confidence interval (CI) estimation. Such testing can done by relying on the definition of CIs: Given an infinite number of...
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