Senior Manager, Data Science - Styling Algorithms

Responsibilities

• Champion bold AI and ML interventions to improve our styling experiences, enabling our stylists to have a multiplicative impact on their client connection points.
• Actively shape the product roadmap for direct client-facing styling experiences, expanding the breadth and depth of personalization touchpoints to complement and inform our human stylists.
• Inspire your team by fostering a culture of ideation, ownership, feedback, and collaboration between team members and with cross-functional partners.
• Work with product managers, other data science teams, UI/UX designers, and business leaders to define and optimize against business objectives for our suite of styling experiences.
• Oversee the end-to-end algorithm development lifecycle, from ideation and experimentation to testing and deployment in a production environment.
• Identify and implement best practices for team collaboration, code quality, use of AI, and data management.
• Stay up-to-date with advancements in AI-assisted development, AI-enabled product experiences, machine learning, and fashion technology.

Requirements

• Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required. Master’s or PhD preferred.
• 5+ years of experience in design and deployment of AI and ML solutions, ideally in retail personalization, with an emphasis on agentic capabilities.
• 2+ years of experience as a team technical lead or direct people manager.
• Ability to write and review production-grade code, ideally in Python.
• Applied knowledge of AI-assisted coding best practices and development of agentic product solutions.
• Excels at building trust with your team, stakeholders, and technical partners.
• Excellent communication skills with the ability to articulate complex technical concepts to business audiences.
• Experience with online A/B testing, experimentation frameworks, and performance metrics.
• Familiar with cloud-based infrastructure and distributed data systems.