Full-Stack Data Scientist, Styling Algorithms

Stitch Fix is redefining retail by blending the art of fashion with the science of machine learning. The Client Experience Algorithms team builds the tools that power personal style, combining best-in-class models with expert human judgment. We foster a culture of ownership where Data Scientists manage the full lifecycle of their work, from research to model deployment. You’ll use multidisciplinary tools to solve complex problems in a data-rich environment, directly influencing how millions of clients discover what they love.

The Styling Algorithms team sits directly at the interface between our technology and models, and our team of over 1500 stylists. We build the recommendations systems and AI assists which help our front-line employees do the right tasks, surface the right merchandise, and communicate effectively with our customers. Our systems make use of frontier AI models, as well as our own industry-leading machine learning models, to serve an experienced and highly-engaged stylist community; which in turn serves over two million active clients.

This role is primarily focused on the recommendation and search engines that power our styling interface. You will be a key contributor to the system that surfaces inventory to our stylists. While you will collaborate closely with the Foundational Models team (who build our base embeddings), you will own the ranking logic, business logic layers, and the deployment of these models into production. You will also prototype and deploy agentic AI workflows to assist stylists in real-time.

This role has a direct impact on the business’s bottom line, and throughout the company's history has been a key source of our innovation and competitive differentiation.

• You will be a primary technical owner of our human-in-the-loop augmented recommendations.
• You will work in a team that embraces both LLMs and traditional ML.
• You will manage experiments to test new features, including communication of results to stakeholders and leadership.
• You will solve problems related to recommendation ranking, hyperparameter optimization, and assortment generation. 
• You can leverage a decade's worth of rich and unique data about our clients, our merchandise, and their interactions.
• You will work with our product, product design, and engineering teams to create roadmaps for developing new client products, user features, and infrastructure.

• You have 3+ years of real-world experience in leveraging Data Science to develop customer-oriented solutions with a recent focus on Recommendation Systems and Search
• You understand the nuances of A/B testing and can balance algorithmic metrics with business metrics.
• You are fluent in SQL and have experience handling large-scale datasets.
• You are proficient in building and deploying apps using the Python data ecosystem.
• You have a degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field.
• You have strong communication skills with business partners.
• You are a team player who sees your growth and success intertwined with the growth and success of your peers.
• You are inspired to take on new challenges and do not shy away from failure.

• We are a group of bright, kind people who are motivated by challenge. We value integrity, innovation and trust. You’ll bring these characteristics to life in everything you do at Stitch Fix.
• We cultivate a community of diverse perspectives— all voices are heard and valued.
• We are an innovative company and leverage our strengths in fashion and tech to disrupt the future of retail. 
• We win as a team, commit to our work, and celebrate grit together because we value strong relationships.
• We boldly create the future while keeping equity and sustainability at the center of all that we do. 
• We are the owners of our work and are energized by solving problems through a growth mindset lens. We think broadly and creatively through every situation to create meaningful impact.
• We offer comprehensive compensation packages and inclusive health and wellness benefits.