Senior Manager, Data Science - AI and Styling Algorithms
New
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Stitch FixRetail Data Science
Remote USAFull-TimeManager
Salary$200,000 — $246,000 USD
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonArtificial IntelligenceMachine LearningData scienceA/B testingDistributed Systems
Requirements
- Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field.
- 5+ years of experience in design and deployment of AI and ML solutions, ideally in retail personalization.
- 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.
- Experience with online A/B testing, experimentation frameworks, and performance metrics.
- Familiar with cloud-based infrastructure and distributed data systems.
- 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.
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.
- Inspire your team by fostering a culture of ideation, ownership, feedback, and collaboration between team members and with cross-functional partners.
- Act as an advocate for our Styling and Merchandising teams, empowering partners to understand trends in stylist feedback and inventory surfacing algorithms.
- Work with product managers, other data science teams, UI/UX designers, and business leaders to define and optimize against business objectives.
- 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.
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