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The curious connection between warehouse maps, movie recommendations, and structural biology

Jesse Clark on

Here at Stitch Fix, we work on many fun and interesting areas of Data Science. One of the more unusual ones is drawing maps, specifically internal layouts of warehouses. These maps are extremely useful for simulating and optimising operational processes. In this post, we'll explore how we are combining ideas from recommender systems and structural biology to automatically draw layouts and track when they change.

Data Science Interns 2017

Sofía Samaniego de la Fuente, Andrew K., Lingrui Gan, and Richard Galvez on

This summer our community included four interns, all graduate students who are passionate about applying their academic expertise to help us leverage our rich data to better understand our clients, their preferences, and new trends in the industry. In this blog post you’ll meet the interns, who will tell you a bit about the problems they worked on and the strategies they used to solve them.

Understanding Failure Modes in Message and Event-based Systems

Dave Copeland on

In a system based on messages or events, there are numerous ways that system can fail, and the techniques needed to handle those failures are different. You can’t just switch messaging infrastructure or use a framework to address all failure points. It’s also important to understand where failures can occur, even if the underlying infrastructure is perfect. Much like acknowledging that there is no happy path, the way you plan for failure affects product decisions.

Genie in a Box : Making Spark Easy for Stitch Fix Data Scientists

Neelesh Salian on

Stitch Fix is a Data Science company that aspires to help you to find the style that you love. Data Science helps us make most of our business and strategic decisions.

Diamond Part II

Tim Sweetser and Aaron Bradley on

Announcing Diamond, an open-source project for solving mixed-effects models

Diamond Part I

Tim Sweetser and Aaron Bradley on

Solving mixed-effects models efficiently: the math behind Diamond

The Biology of Code

Ellie Bahadori on

It seems like the endless stream of data in a terminal is the farthest thing from a living, breathing being. Looking through the Stitch Fix codebase, what comes to mind is structures, information systems, methods of exchange – not a group of finches on a faraway Galapagos island.

Nodebook

Kevin Zielnicki on

Analysis should be reproducible. This isn’t controversial, and yet irreproducible analysis is everywhere. I’ve certainly created plenty of it. Why does this happen, despite good intentions? Because, in the short term, it is easier and more expedient not to worry about reproducibility. But this isn’t a moral failing so much as a failing of our tools. Tools can, and should, help make reproducible analysis the natural thing to do. As a step towards encouraging reproducibility, this post introduces Nodebook, an extension to Jupyter notebook.

Inventory Time Machine

Sky Yin on

As a proudly data-driven company dealing with physical goods, Stitch Fix has put lots of effort into inventory management. Tracer, the inventory history service, is a new project we have been building to enable more fine-grained analytics by providing precise inventory state at any given point of time...

This one weird trick will simplify your ETL workflow

Russell Avdek on

In this post aimed at SQL practitioners who would rather spend their time writing Python, we'll show how a web development tool can help your ETL stay DRY.