Senior Manager, Recommendation Algorithms

Stitch Fix (NASDAQ: SFIX) 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 Recommendation Algorithms team powers personalized shopping experiences across Stitch Fix, using machine learning and AI to help clients discover items and outfits they’ll love. The team turns model outputs, inventory, client context, and business objectives into relevant recommendations, rankings, search results, and personalized assortments across Fix and Freestyle.

As the Senior Manager, Recommendation Algorithms, you will lead a team of Data Scientists and Machine Learning Engineers responsible for the strategy, development, and production performance of these client-facing personalization systems. You’ll partner closely with Product, Engineering, Merchandising, Enterprise Analytics, and other Algorithms teams to improve recommendation quality, evolve our technical approach, and deliver measurable client and business impact.

• Lead the strategy and execution of client-facing personalization across recommendations, ranking, search, discovery, outfits, and similar-item experiences, balancing relevance, diversity, freshness, inventory availability, client context, and business objectives.
• Shape the roadmap with Product, Engineering, Design, Merchandising, Analytics, and Algorithms partners, making thoughtful tradeoffs across client experience, stylist needs, inventory objectives, recommendation quality, and system complexity.
• Drive rigorous experimentation and measurement through offline evaluation and online A/B testing, using metrics such as engagement, selection, keep rate, items sold, revenue, margin, and client satisfaction to guide decisions and improve outcomes.
• Own the end-to-end algorithm lifecycle, from opportunity sizing and modeling through experimentation, production deployment, monitoring, and operational support, while partnering with Engineering to build scalable, reliable, observable, and explainable recommendation systems.
• Advance how the team uses AI and emerging technologies, including generative AI and LLM-based evaluation, to improve semantic understanding, recommendation and outfit quality, model evaluation, and team productivity while fostering a culture of technical excellence, ownership, learning, and collaboration.

This is what you’ll need to succeed in this role from day one.

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Physics, Operations Research, or another quantitative field;
  Master’s degree or PhD preferred.
• 5+ years of experience designing and deploying machine learning solutions, ideally within recomm