Thoughtfully writing a blog post

Let Curiosity Drive: Fostering Innovation in Data Science

How to create an environment to empower your data scientists to come up with ideas you’ve never dreamed of.

Multithreaded in the Wild

See who's out in the wild for the month of January

Your Client Engagement Program Isn't Doing What You Think It Is.

This post explores the use of multi-arm and contextual bandits as a framework for structuring outreach and client engagement programs.

Putting the Power of Kafka into the Hands of Data Scientists

How Stitch Fix designed and built a scalable, centralized and self-service data integration platform tailored to the needs of their Data Scientists.

Synesthesia: The Sound of Style

If we could assign sounds to items of clothing, what would a Fix sound like?

Understanding Latent Style

This post explores the use of matrix factorization not just for recommendations, but for understanding style preference more broadly.

Add Constrained Optimization To Your Toolbelt

This post is an introduction to constrained optimization aimed at data scientists and developers fluent in Python, but without any background in operations research or applied math. We'll demonstrate how optimization modeling can be applied to real problems at Stitch Fix. At the end of this article, you should be able to start modeling your own business problems.

Two things about power

Experimenter beware: Running tests with low power risks much more than missing the detection of true effects.

Lumpers and Splitters: Tensions in Taxonomies

As data scientists tasked with segmenting clients and products, we find ourselves in the same boat with species taxonomists, straddling the line between lumping individuals into broad groups and splitting into small segments. The approach for drawing the boundaries needs to take into account signals from the data while maintaining sharp focus on the project needs. A balance between lumping and splitting allows us to make the best data-driven decisions we can with the resources we have...

What Do Data Scientists Need to Know about Containerization? As Little as Possible.

Data scientists are not always equipped with the requisite engineering skills to deploy robust code to a production job execution and scheduling system. Yet, forcing reliance on data platform engineers will impede the scientists autonomy. If only there was another way. So today, we're excited to introduce Flotilla, our latest open source project...