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As a Strategic Training & Quality Intern, you will enhance knowledge management, analyze data for customer insights, and support brand reputation efforts, ensuring a seamless customer experience.

Lead and elevate user research during maternity cover: coach teams, validate and run end-to-end qualitative and quantitative studies (~40% time), maintain the insights repository, translate psychographic segmentation into product actions, and promote findings to influence product strategy and stakeholder decisions.

Review and validate listings for unsigned brands, verify AI model detections and compliance, research brands, prioritize product flow, contribute to new curation scope, and collaborate on continuous catalog improvement and training.

The Staff Data Scientist will develop AI models to enhance operational workflows and customer experiences, focusing on quality and authenticity detection through advanced ML techniques, collaborating with cross-functional teams, and mentoring junior data scientists.

The Staff Data Scientist will develop AI models for product quality verification and enhance customer interactions. Responsibilities include designing solutions, collaborating with teams, evaluating models, and mentoring juniors while utilizing expertise in machine learning and computer vision.

Lead Vestiaire Collective's Brand Partnerships during a maternity cover period: manage business development and account management, oversee strategic partner relationships, drive partner performance using data, coordinate cross-functional execution, manage and develop a small team, support commercial negotiations and renewals, and represent the team internally and externally to expand luxury resale partnerships.

Build foundational MLOps infrastructure and deploy multi-model CV and VLM systems for authentication and fraud detection. Design data/feature management, model tracking, serving, monitoring, and automated retraining pipelines. Scale ML capabilities for search, recommendations, pricing, and marketing while ensuring low-latency, high-throughput production services and strong engineering hygiene.

Build foundational MLOps infrastructure and deploy/scale heavy-width CV and VLM models for luxury product authentication and fraud detection. Design data/feature management, model registry, serving, monitoring, and automated retraining pipelines. Evaluate tooling vs enterprise platforms, ensure low-latency high-throughput inference, and centralize ML engineering support across search, recommendations, pricing, and marketing while mentoring teams and enforcing engineering hygiene.