Blog posts about Data Science

For every initiative that a business takes on, there is an opportunity potential and a cost—the cost of not doing something else. But how do you tangibly determine the size of an opportunity? Opportunity sizing is a method that data sci...

By Eric Fung and Diego Castañeda Shopify Inbox is a single business chat app that manages all Shopify merchants’ customer communications in one place, and turns chats into conversions. As we were building the product it was essential fo...

At Shopify, we recognize the positive impact data-informed decisions have on the growth of a business. But we also recognize that data exploration is gated to those without a data science or coding background. To make it easier for our m...

In this blog post we present a way to version your Airflow DAGs on a single server through isolated pipeline and... ...

Our mission at Shopify is to make commerce better for everyone. Doing this in the long term requires constant learning and development – which happen to be core values here at Shopify. Learning and development aren’t exclusively interna...

By Megan Parker and Sam Wheating Apache Airflow is an orchestration platform that enables development, scheduling and monitoring of workflows. At Shopify, we’ve been running Airflow in production for over two years for a variety of work...

Recently we launched Shopify Balance, a money management account and card that gives Shopify merchants quick access to their funds with no fees. After the beta launch of Shopify Balance, the Shopify Data team was brought in to answer the...

People often equate data science with statistics, but it’s so much more than that. When data science first emerged as a craft, it was a combination of three different skill sets: science, mathematics, and art. But over time, we’ve drifte...

Shopify's machine learning platform team builds the infrastructure, tools and abstracted layers to help data scientists streamline, accelerate and simplify their machine learning workflows. There are many different kinds of machine learn...

If you’re a data scientist on a product team, much of your work involves getting a product ready for release. You may conduct exploratory data analyses to understand your product’s market, or build the data models and pipelines needed to...

TL;DR: Using the properties of the Poisson bootstrap algorithm and quantile estimators, we have been able to reduce the computational [...]

 by: Yaroslav Tkachenko, Kevin Lam, and Rafael Aguiar At Shopify, we’ve adopted Apache Flink as a standard stateful streaming engine that powers a variety of use cases like our BFCM Live Map. Our Flink applications are deployed in a Kub...

At Spotify, we aim to build and improve our product in a data-informed way. To do that, teams are encouraged [...]

Five years ago, my team and I launched the first machine learning product at Shopify. We were determined to build an algorithm-powered product that solved a merchant problem and made a real impact on the business. Figuring out where to s...

Co-authors: Varun Saxena, Harikumar Velayutham, and Balamurugan Gangadharan LinkedIn is the largest global professional network and generates massive amoun...

Co-authors: Varun Saxena, Harikumar Velayutham, and Balamurugan Gangadharan LinkedIn is the largest global professional network and...

You’ve probably seen the “Data Science Hierarchy of Needs” (pictured below) before. Inspired by Maslow, it shows the tooling you would use at different levels in data science—from logging and user-generated content at the bottom, to AI a...

By Ashay Pathak and Selina Li Tens of thousands of merchants use Shopify Inbox as a single business chat app for all online customer interactions and staff communications. Over four million conversations were exchanged on Shopify Inbox ...