Full-Stack Data Scientist, Styling Algorithms

Stitch Fix

United States

United States

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À propos

SFIX) is the leading online personal styling service that helps people discover the styles they will love that fit perfectly so they always look - and feel - their best. Few things are more personal than getting dressed, but finding clothing that fits and looks great can be a challenge. By pairing expert stylists with best-in-class AI and recommendation algorithms, the company leverages its assortment of exclusive and national brands to meet each client's individual tastes and needs, making it convenient for clients to express their personal style without having to spend hours in stores or sifting through endless choices online. Stitch Fix, which was founded in 2011, is headquartered in San Francisco. 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. 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. 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 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 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. We value integrity, innovation and trust. 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 boldly create the future while keeping equity and sustainability at the center of all that we do. This role will receive a competitive salary, benefits, and equity. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance. This position is eligible for an annual bonus, and new hire and ongoing grants of restricted stock units, depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site.
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leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts between health plans and healthcare providers. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data. Please review Stitch Fix's US Applicant Privacy Policy and Notice at Collection here: Recruiting Fraud Alert: To all candidates: your personal information and online safety are top of mind for us. Recruiters will never request payments, ask for financial account information or sensitive information like social security numbers.

United States

Compétences linguistiques

English

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