The Algorithms Platform team builds the tools that makes deep integration of data science into all areas of our business possible. We are responsible for designing the technical systems that shape and guide how data scientists impact our strategy, operations, and decision making. Because data scientists at Stitch Fix are encouraged (and expected!) to rapidly explore ideas and hypotheses, they need an environment in which they can easily iterate cycles of design, create, and test. They should be confident in building, deploying, and supporting algorithms in live production systems independently.
To make this happen, Algorithms Platform has to anticipate data scientists' needs before the scientists know they have them. We have to have a 360-degree view of how data science is done at Stitch Fix (and its relationship to the overall business) and figure out how to make it better. We use this perspective to frame, design, and build reliable systems that are powerful, easy to use, and constantly improving. We are our own product and project managers, both creating a vision of what should be built and turning that vision into reality. As our business grows and changes, some of the time we have to rethink the capabilities and interfaces that data scientists currently use and "re-platform" to better tools and infrastructure.
If this sounds exciting to you, then let us know! We are looking for powerful engineers who are excited to engage in difficult challenges and can ship products. In particular, we are looking for folks who:
- Are willing to challenge the status quo to propose new and better ways of doing things, and have the rigor to show us why.
- Have an open mind and discerning attitude to figure out what is really needed rather than simply build that which is asked for.
- Jump in to solve a problem even when conditions are not optimal.
- Can look holistically at systems and architectures to decide what to improve, replace, and remove.
- Are interested in learning how to make our business better by designing, coding, communicating, and educating to make that happen.
- Are motivated to learn new tools and systems, especially when they are better than the old ones.
- Can deliver early and often because they know that iterating on the "good" is far better than waiting a long time for the "perfect".
- Want to work cooperatively in a team and in collaboration with business partners.
- Appreciate a working environment with high ethical standards and a culture of kindness.
ABOUT ALGORITHMS PLATFORM
Our Algorithms Platform team is composed of focused subteams, all of whom often partner with data scientists and each other to deliver solutions that are carefully tuned to our business needs. Projects often include members of multiple teams.
- ALGO-UI: This team is a small, nimble group of UI engineers that is focused on enabling our data scientists to communicate their insights to the rest of the organization. They have autonomy to build and deploy whatever tools they deem appropriate to the situation, from custom React / D3 web applications, to dashboards written in Shiny, to ambient displays.
- ALGO-DEV: This team is focused on building platforms to enable data scientists to more easily create, integrate, deploy, manage, and evaluate their models. They have wide latitude to choose how they go about enabling our data scientists; everything that influences how a model is built, how its predictions are served, how it integrates with the business and other algorithms, to how it's A/B tested, is fair game for them to touch.
- SCALABLE INFRASTRUCTURE: This team provides frameworks and services to access and operate on our data, including Spark, Presto, and custom tools. This team also handles initial data ingestion: our data initially comes from our Kafka logging pipeline along with regular snapshots of transactional databases. Our ETL framework along with tools to track and monitor jobs helps to increase reliability while making it easier for data scientists to obtain and manipulate data.
- SCIENTIFIC WORKING ENVIRONMENT: This team is responsible for curating, designing, building, and supporting the day-to-day operating environment for our data scientists. This includes workflows/ETL, adhoc tooling and computation, management of data and code, and collaboration between data scientists.