Multi-Armed Bandits and the Stitch Fix Experimentation Platform
We've recently built support for multi-armed bandits into the Stitch Fix experimentation platform. This post will explain how and why.
We've recently built support for multi-armed bandits into the Stitch Fix experimentation platform. This post will explain how and why.
Incorporating opportunity costs when running experiments
How many sets of 5 can you make from 10,000 distinct items? Recall that chapter about permutations and combinations...
This post explores the use of matrix factorization not just for recommendations, but for understanding style preference more broadly.
When I started playing with word2vec four years ago I needed (and luckily had) tons of supercomputer time. But because of advances in our understanding of word2vec, computing word vectors now takes fifteen minutes on a single run-of-the-mill computer with standard numerical libraries1. Word vectors are awesome but you don't need a neural network -- and definitely don't need deep learning -- to find them. So if you're using word vectors and aren't gunning for state of the art or a paper publication then stop using word2vec.
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.
How to organize an office so everyone working there can be comfortable and productive is the topic of much discussion. A common strategy is to seat people by their team or sub-team membership. Another strategy which we have been employing is to simply allocate people randomly. Building upon these experiences we've developed a new seating allocation tool "seetd", that allows us to frame this as an optimization problem. We're now free to combine these and other approaches objectively.
How data science is woven into the fabric of Stitch Fix. In this interactive tour we share ten “stories” of how data science is is integral to our operations and product.
When people think of “data science” they probably think of algorithms that scan large datasets to predict a customer’s next move or interpret unstructured text. But what about models that utilize small, time-stamped datasets to forecast dry metrics such as demand and sales? Yes, I’m talking about good old time series analysis, an ancient discipline that hasn’t received the cool “data science” rebranding enjoyed by many other areas of analytics.
“What is the relationship like between your team and the data scientists?” This is, without a doubt, the question I’m most frequently asked when conducting interviews for data platform engineers. It’s a fine question – one that, given the state of engineering jobs in the data space, is essential to ask as part of doing due diligence in evaluating new opportunities. I’m always happy to answer. But I wish I didn’t have to, because this a question that is motivated by skepticism and fear.