2019年11月21日 · At Stitch Fix, the Algorithms team is a standalone organization. This enables us to not only work on a range of interesting problems (marketing spend optimization, conversion optimization, warehouse capacity, and freight cost optimization), but also to identify the cases in which the key business tradeoffs may span multiple departments.

2015年7月30日 · The random forest curve does not look very intuitive: Final Words As stated in the introduction, the purpose of this post is to get more data scientists to use GAM. Hopefully, after reading this post, you’ll agree that GAM is a simple, transparent, and flexible modeling technique that can compete with other popular methods.

2016年3月16日 · So, why don’t we fix it? Why does every data science and algorithms development team seem to slide into the same dysfunctional model? I blame two things, offered here in the form of a couple observations: You Probably Don’t Have Big Data Data processing tools and technologies have evolved massively over the last five years.

2016年8月15日 · It’s much harder to know when you’re over-engineering. The root cause of this is expanding the problem at hand so that the solution is much more interesting than the solution to the actual problem. But, what does “over-engineering” even mean? A basic definition might be doing more work than is necessary to solve the problem at hand.

2023年3月6日 · At Stitch Fix, we are constantly exploring innovative ways to utilize the latest advancements in AI and ML to enhance the experiences of our clients. In this blog post, we will delve into our approach to generative AI, with a special focus on our text generation use cases.

2016年3月3日 · At Stitch Fix, we have found similar patterns of variations, not only among clothing but also among our customers with a shared size label. In the chart below, we plot chest width and body length measurements of 180 Stitch Fix blouses (on the left), and 5,000 randomly generated body dimensions and size labels that represents our customer base.

2022年2月22日 · A few months ago we released Hamilton, Stitch Fix’s open-source microframework [1] for managing dataflows. With feedback from the community, we’ve implemented a variety of new features that make it more general purpose for Data Science/Data Engineering teams. Importantly, Hamilton now operates over any python object types, and can integrate with a variety of distributed compute platforms ...

2019年8月19日 · A constrained time and cost; and The ability to be undone or rolled back with a minimum of cost and effort; the artifacts of such an experiment are likely to be short-lived and replaced with more maintainable and production-ready code. Every technology decision that we make has ripple effects beyond the code in which it manifests.

2015年11月15日 · Stitch Fix’s take-home challenge was a fantastic expression of what the company valued overall in a candidate. I knew from the challenge that my ability to understand what folks at the other end of the screen needed would be vital, and that Stitch Fix saw good code as a means to help people and not an end unto itself.

2020年3月2日 · At Stitch Fix, algorithmic capabilities aren’t so much designed or envisioned as they are discovered and revealed through curiosity-driven tinkering by data scientists. Our organizational strategies center on enabling this bottom-up innovation. Hence, we call this visualization “Cultivating Algorithms”.