How not to fail your online controlled experimentation — Online experimentation has become the industry standard for product innovation and decision-making. With well-designed A/B tests, tech companies can iterate their product lines quicker and provide better user experiences. Among FAANG, Netflix is the company most open about its experimental approach. In a series of posts, Netflix has introduced…

Best practices that data scientists should follow pre-, during-, and after- experiments — Introduction Randomized Controlled Trials (aka. A/B tests) are the gold standard of establishing causal inference. RCTs strictly control for the randomization process and ensure equal distributions across covariates before rolling out the treatment. Thus, we can attribute the mean difference between the treatment and control groups to the intervention.

A statistical approach to A/A tests — Introduction A rigorous process of experimentation, aka., A/B tests, has become trendy and widely adopted in the tech sector. As the early adopters, FAANG companies have incorporated experimentation into their decision-making process. For example, Microsoft Bing conducts A/B tests on 80% of its product changes. Google resorts to experimentation to…

Three solutions from Lyft, LinkedIn, and Doordash — Introduction A rigorous process of A/B testing generates valuable insights about consumer behaviors directly related to the success of a product. …

5 key takeaways to boost your tech career — Introduction If you have followed me for a while, you probably know I started out as a Data Scientist at Walmart Global Tech, the technology branch of the Fortune 1 company. It was my first industry job out of academia. Like everyone else who began a new career chapter, I found…

Climb up the ladder of causation — Nobel Prize Goes To … By now, you should have heard that three Economics methodologists — David Card, Joshua Angrist, and Guido Imbens — won the Nobel Prize. Their contributions to research methodology (i.e., Causal Inference) both cheer up and puzzle the data community: What is Causal Inference anyway? How does it differ from other…

The aftermath and the coping strategy — Introduction First off, here is a big personal update: in March 2022, I officially graduated from my Ph.D. program and earned the doctoral title. So, please address me as Dr. Ye since today (kidding). While looking back at the long journey, surviving grad school takes more than hard work and dedication…

Data Scientists are cool! — Introduction A recent trend in the tech sector is companies increasingly resort to scientific methods to guide decision-making. In particular, they adopt a rigorous testing strategy for product release and innovation. The underlying idea is: Whenever in doubt, A/B tests it. To meet large-scale testing needs, tech companies build in-house…

And what to expect in 2022 — I simply cannot imagine it is the time of the year again that everyone tries to brag about their year-long achievements and make wishful resolutions for the coming year that they mostly cannot keep. Well, I’m not an exception to the great tradition. 2021 has been a year of…