Dia&Co is the leading personalized styling service for women who wear sizes 14+. Our business meets a profound need, and we are on a mission to democratize fashion — not only by providing easy access to quality clothing, but also by building an inclusive community of women who use fashion to celebrate their bodies.
Each team is asked to select, explain, and rank their top 8 values in order of importance.
Customer Comes First
Our mission is to bring the best in plus-size fashion to a population that’s been underserved for far too long.
Women sizes 14 and up are over 50% of the population of the US, yet on average they spend significantly less on fashion than their lower sized counterparts. The lack of product variety, poor/demeaning in-store experiences, and societal pressure all contribute to this. These are the problems we are solving for this customer every day at Dia. Every feature we build, every machine learning system we create, and every flow we optimize is aimed at improving the the customer experience. Engineers are fundamental to this process, and are expected to be looking at the data and thinking about the customer for each thing we build. We even style boxes for our customers as part of our onboarding!
We collect and use data at every step of our process.
Everything from the profile survey questions a customer initially fills out to the feedback and ratings they provide for each piece we send them is measured and tracked. Data and machine learning is used to solve our cold start problems, improve the items we send out on subsequent boxes (our system gets smarter each time), improve efficiency of our operation, and even to make our own clothes. Almost all of our product roadmap is driven by data analytics. We are constantly running AB tests and evaluating results in order to inform the next step of feature iteration.
High Quality Code Base
Being just over a 2-year-old company means we don’t have much legacy code.
We’re currently at 96% unit test coverage of our entire codebase. Testing is fundamental to our culture, and engineers are expected to not only write tests for all their code, but also manually test each feature they develop. We run lean when it comes to manual QA testers, as this isn’t scalable.
We believe the most important part of being an engineer is being productive and happy over the long term.
Many of our engineers work remotely or semi-remote in order to take care of family, or just to focus without typical office distractions. We have a flexible vacation policy with no fixed number of days, and typical office hours for folks is 10am to 6pm. We also do team outings and lunches every month or so. Our most recent was an Escape-the-Room that combined our eng and data teams!
High Employee Retention
We maintain a strong engineering culture.
You can read about it on our blog. This has led to extremely high retention on our teams. In fact, you can read about our company Core Values and how our team works with them.
We also value having diverse and talented engineering and data teams. About 40% of both teams are women, and consists of people based in both New York and Los Angeles.
Uses Agile Methodologies
Our eng teams are divided into pods based on major product areas.
Each pod has a sprint that is typically two weeks in length, and we do estimation/retros and story grooming for each sprint. Our team leads and product managers typically collaborate closely to run each of those meetings. Pods are also free to experiment with changes to the structure -- they often test out a change for a few sprints then evaluate if it’s worth keeping or not.
Data teams (analysts, data scientists, data engineers) typically work in a kanban system, as their projects tend to span longer timeframes.
Rapidly Growing Team
We are planning to double the size of our engineering/data teams, as the company has been growing considerably.
Our projects range from new customer features, warehouse routing optimization algorithms, creating React components for our styling system, and a lot more! We’re looking for talented engineers and data folks in all areas -- from consumer-facing, to internal styling and operations. Email Lana Herzig at: [email protected] if you’re interested!
We are constantly pushing to production.
Whenever a feature is ready and has been tested in our staging environment, we typically push it live asap. We have a modern CI/CD process that integrates CircleCI and AWS to get code out quickly. We make use of feature flags when needed in order to keep our deploys compact and small. New hires can expected to be shipping to production within their first couple weeks.