Director, Data Science & Algorithms - CX Product Experiences

Stitch Fix•San Francisco, CA

12d

About The Position

Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential. The Client Experience Product Algorithms team is responsible for the machine learning, AI, experimentation, and product analytics capabilities that power personalized experiences for Stitch Fix clients and stylists. Partnering across Product, Engineering, Design, Styling, Marketing, Merchandising, Finance, Enterprise Analytics, Data Platform, and DSN, the team translates data and algorithms into measurable business impact. As Director, Product Algorithms, you will lead the strategy, execution, and people behind our Growth, Styling, and Fix & Freestyle Algorithms portfolios. You'll define how AI, machine learning, experimentation, and analytics shape the future of personalized shopping while building the operating discipline, technical excellence, and cross-functional alignment needed to deliver scalable business results.

Requirements

Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related quantitative field; advanced degree preferred.
10+ years of experience in data science, machine learning, experimentation, product analytics, AI, or algorithmic product development, including 5+ years leading teams and experience managing managers or senior technical leaders.
Demonstrated success defining strategy and delivering production machine learning, AI, personalization, or experimentation capabilities that drive measurable product and business outcomes.
Strong technical fluency across modern machine learning, generative AI/LLMs, experimentation methodologies, product analytics, and production algorithmic systems.
Experience building cross-functional partnerships with Product, Engineering, Design, Analytics, Data Platform, Marketing, Merchandising, Finance, and executive stakeholders.
Exceptional strategic thinking, communication, prioritization, problem-solving, and organizational leadership skills, with the ability to influence across technical and non-technical audiences.
Experience using AI tools (such as ChatGPT, GitHub Copilot, or similar technologies) to improve productivity, decision making, collaboration, and the quality of work.
This position requires the ability to sit for extended periods of time, use a computer and standard office equipment, and communicate effectively in both written and verbal formats.

Nice To Haves

Advanced degree (MS or PhD) in Computer Science, Machine Learning, Statistics, Operations Research, Engineering, or a related field.
Experience leading AI- or ML-driven consumer products within e-commerce, marketplaces, retail, recommendations, personalization, or digital consumer experiences.
Experience building or evolving experimentation platforms, product analytics capabilities, or AI governance and operational excellence practices.
Familiarity with large-scale recommendation systems, ranking models, generative AI applications, causal inference, optimization, or reinforcement learning.
Experience leading organizations through significant technical transformation, organizational scaling, or AI adoption initiatives.

Responsibilities

Lead the Product Algorithms portfolio across Growth, Styling, and Fix & Freestyle, setting strategy and driving measurable outcomes across acquisition, engagement, retention, styling quality, Fix, Freestyle, outfitting, and related commerce experiences.
Define the vision and roadmap for applying data science, machine learning, AI, experimentation, and product analytics to improve client experiences, stylist effectiveness, and business performance.
Drive innovation by identifying, evaluating, and scaling modern AI, machine learning, personalization, and experimentation techniques that create meaningful impact while balancing technical feasibility, execution capacity, and business priorities.
Strengthen organizational effectiveness by improving planning, prioritization, experimentation practices, product analytics capabilities, operational readiness, incident management, and cross-functional decision making across the portfolio.
Build and develop a high-performing organization of managers and senior individual contributors, fostering technical excellence, strong product leadership, accountability, and collaborative partnerships while representing Product Algorithms with executive stakeholders.
Use AI-powered tools (such as ChatGPT, GitHub Copilot, and other emerging technologies) to improve decision making, productivity, communication, and operational efficiency.
Leverage experimentation platforms, analytics tools, machine learning infrastructure, and product development systems to guide roadmap decisions and measure business impact.
Continuously evaluate and adopt new AI capabilities, technologies, and ways of working that improve team effectiveness and accelerate innovation.