Principal Full-Stack Data Scientist – Foundational Models

🔥 18 hours ago

🇺🇸 United States – Remote

💵 $200k - $237k / year

⏰ Full Time

🔴 Lead

📊 Data Scientist

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This company has sponsored H1B visas in the past.

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Stitch Fix

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2011

📣 Marketing

📦 Logistics

💼 Consulting

💰 $36.9M Venture Round on 2017-11

Marketing • Logistics • Consulting

Stitch Fix is a personal styling service that offers a unique and personalized approach to fashion for women, men, and kids. Clients start by taking a style quiz, which helps Stitch Fix understand their preferences, sizes, and budget. Based on this information, a personal stylist selects five personalized clothing pieces that are shipped directly to the client's door. Customers can choose to keep and purchase any items they like, with the $20 styling fee applicable to kept items. Stitch Fix carries a wide range of sizes and offers free shipping and returns. The service is flexible, with no subscription required, allowing customers to order style boxes on demand or at regular intervals. Stitch Fix also offers a 'Freestyle' shopping option where clients can browse curated suggestions based on their preferences. The company covers a wide variety of styles from numerous brands, ensuring there are options to suit various fashion tastes and needs.

📋 Description

• Design, develop, evaluate, and productionize machine learning models improving personalization and recommendation systems • Advance foundational modeling capabilities, including client and item representations, embeddings, retrieval, ranking, recommendation models, and assortment generation • Explore and apply LLMs, deep learning, representation learning, multimodal modeling, and generative approaches • Own the full ML lifecycle from problem formulation and data exploration through modeling, experimentation, deployment, monitoring, and iteration • Design offline evaluations and online experiments to measure model performance and client and business impact • Work with large-scale behavioral and product datasets using Python, SQL, and distributed data-processing tools • Build production-quality ML solutions emphasizing scalability, reliability, latency, observability, and cost • Collaborate with Product, Engineering, and Data Science teams to translate downstream needs into reusable foundational ML capabilities • Contribute to technical direction through design discussions, code reviews, research, prototyping, and best practices • Communicate technical concepts, modeling approaches, tradeoffs, and recommendations to technical and non-technical stakeholders • Mentor and collaborate with Data Scientists and engineers

🎯 Requirements

• Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required • 8+ years of experience in design and deployment of machine learning solutions, ideally in personalization, recommendation systems, representation learning, or search • Strong ability to architect technical solutions and write production-grade code in Python • Ability to independently drive ambiguous machine learning problems from initial exploration and prototyping through production deployment, monitoring, iteration, and measurable impact • Experience working with large-scale datasets using SQL and distributed data-processing technologies such as Spark • Experience with modern deep-learning frameworks such as PyTorch or TensorFlow • Strong understanding of model evaluation and experimentation, including offline evaluation, A/B testing, and translating model improvements into measurable product or business outcomes • Ability to reason about production ML system tradeoffs, including model quality, latency, scalability, reliability, and computational cost • Strong communication and collaboration skills, with the ability to influence technical decisions and communicate complex concepts to technical and non-technical stakeholders • Intellectual curiosity and demonstrated ability to learn and apply new machine learning techniques to practical problems

🏖️ Benefits

• Competitive salary • Equity • Annual bonus • New hire and ongoing restricted stock unit grants, depending on employee and company performance • Medical benefits • Dental benefits • Vision benefits • Other inclusive health and wellness benefits • Comprehensive compensation package

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