Remote opportunity at
Stitch FixPrincipal Full-Stack Data Scientist - Foundational Models
Stitch Fix operates in the retail sector by integrating human styling expertise with advanced machine learning and Generative AI to deliver personalized shopping experiences. The organization…
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About This Role
Stitch Fix operates in the retail sector by integrating human styling expertise with advanced machine learning and Generative AI to deliver personalized shopping experiences. The organization is currently seeking a Principal Full-Stack Data Scientist for its Foundational Models team on a full-time, remote basis. In this role, you will take ownership of the entire machine learning lifecycle, focusing on foundational systems that drive personalization, item and client representations, ranking, and…
Job Description
Stitch Fix operates in the retail sector by integrating human styling expertise with advanced machine learning and Generative AI to deliver personalized shopping experiences. The organization is currently seeking a Principal Full-Stack Data Scientist for its Foundational Models team on a full-time, remote basis.
In this role, you will take ownership of the entire machine learning lifecycle, focusing on foundational systems that drive personalization, item and client representations, ranking, and retrieval. Your daily work involves designing, developing, evaluating, and deploying production-grade machine learning models, including deep learning techniques and large language models. You will tackle complex problems involving large-scale behavioral, transactional, visual, and textual datasets while collaborating closely with engineering, product, and data science colleagues.
This position is well-suited for an experienced practitioner who enjoys hands-on modeling and architectural challenges, ranging from offline evaluations and online A/B testing to cost and latency optimization. The annual salary range is set at $200,000 to $237,000, supplemented by an annual bonus and restricted stock unit grants.
Responsibilities
- Design, develop, evaluate, and productionize machine learning models for personalization and recommendation systems
- Advance core foundational modeling elements including client and item representations, embeddings, retrieval, ranking, and assortment generation
- Apply deep learning, representation learning, multimodal modeling, generative approaches, and large language models to improve system performance
- Manage the complete machine learning lifecycle from problem formulation through data exploration, modeling, experimentation, deployment, monitoring, and iteration
- Conduct offline evaluations and online experiments to measure client and business impact
- Write production-grade code in Python and process large-scale datasets using SQL and distributed frameworks like Spark
- Collaborate with Product, Engineering, and fellow Data Science teams to build reusable foundational capabilities
- Contribute to technical direction through design reviews, prototyping, research, and setting modeling best practices
- Communicate complex technical concepts, trade-offs, and strategic recommendations to technical and non-technical stakeholders
- Mentor and collaborate with other data scientists and engineers
Requirements
- Minimum of 8 years of professional experience in designing and deploying machine learning solutions within personalization, search, recommendation systems, or representation learning
- Strong capability to architect technical solutions and write production-grade Python code
- Demonstrated ability to independently manage ambiguous machine learning problems from inception to production deployment and measurable impact
- Practical experience utilizing SQL and distributed data-processing tools such as Spark for large-scale datasets
- Familiarity with modern deep learning frameworks like PyTorch or TensorFlow
- Solid understanding of model evaluation, experimentation methodologies, A/B testing, and translating model upgrades into business outcomes
- Ability to balance production tradeoffs including model quality, latency, scalability, reliability, and computational cost
- Strong communication and collaboration skills to influence technical decisions across stakeholders
Qualifications
- Bachelor’s degree in a quantitative field such as Statistics, Computer Science, Mathematics, Physics, or a related discipline
- Master’s degree or PhD in a quantitative field
Core Skills
Benefits
- Annual bonus eligibility
- New hire and ongoing grants of restricted stock units
- Medical, dental, and vision insurance
- Inclusive health and wellness benefits
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this position remote?
Yes, the posting explicitly lists the remote status for this role as remote.
What is the salary range for this role?
The salary for US-based employees hired into this position ranges from $200,000 to $237,000 per year, depending on factors such as location, experience, professional background, and performance.
What educational qualifications are preferred?
While a bachelor's degree in a quantitative field like Computer Science, Statistics, Physics, or Mathematics is required, a Master's degree or PhD is preferred.
What additional compensation is offered beyond base salary?
The position is eligible for an annual bonus as well as new hire and ongoing grants of restricted stock units, subject to employee and company performance.
Sample Interview Questions
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