Staff Data Scientist

Vestiaire Collective is the leading global online marketplace for desirable pre-loved fashion. Our mission is to transform the fashion industry for a more sustainable future by empowering our community to promote the circular fashion movement. Vestiaire was founded in 2009 and is headquartered in Paris with offices in London, Berlin, New York, Singapore, Ho Chi Minh and Hong Kong and warehouses in Tourcoing (France), Crawley (UK), Hong Kong and New York.We currently have a diverse global team of 700 employees representing more than 50 nationalities. Our values are Activism, Transparency, Dedication and Greatness and Collective. We are proud to be a BCorp.About The RoleWe are seeking a highly skilled and experienced Staff Data Scientist to join our Operations and Customer Service department. You will be instrumental in developing advanced AI models that enhance both internal operational workflows and customer-facing experiences. This includes building systems that help our Curation team verify product quality and authenticity from customer-provided descriptions and images, as well as exploring and delivering new models aimed at improving how customers interact with our platform. The role requires strong end-to-end machine learning expertise and a user-centric mindset to drive measurable improvements in accuracy, operational efficiency, and overall customer experience.What you will do Design and own end-to-end AI/ML solutions for item quality and authenticity detection, spanning:Image analysis (detecting marks, defects, wear, size inconsistencies) T ext and metadata understanding (brand, sizing, category anomalies) Counterfeit and fraud detection modelsDesign, prototype, and iterate on AI models that directly power and improve customer-facing experiences on our platform (e.g., smarter assistance) Collaborate closely with the Product and Curation teams to define requirements, integrate AI models into their workflow, and provide insights to enhance their verification processes Advise and direct data/feedback collection for continuous improvement and monitoring of the performance of the models Perform rigorous model evaluation, A/B testing, and continuous improvement of AI models Work with engineering teams to ensure seamless deployment and integration of AI models into our existing platforms Research and stay updated on the latest advancements in AI, machine learning, deep learning and computer vision to identify new opportunities and best practices Mentor senior and mid-level data scientists, raising the technical bar on modeling, data quality, and experimentation best practices Communicate complex technical concepts and findings to both technical and non-technical stakeholdersWho you are 6+ years of experience in data science, machine learning engineering, or AI development, with a strong focus on computer vision applications and customer facing models Deep expertise in applied AI/ML (computer vision, anomaly detection, fraud/risk modeling).Track record of leading technical initiatives and influencing decisions across teams Experience in architecturing, deploying, and maintaining AI systems at scale Proficiency in programming languages such as Python and experience with relevant libraries/frameworks (e.g., TensorFlow, TorchServe, TensorflowServing, PyTorch, scikit-learn, spaCy, Hugging Face Transformers, OpenCV) Deep understanding of machine learning algorithms, statistical modeling, and data manipulation techniques Experience with data visualization tools and communicating insights effectively Strong problem-solving skills, with the ability to tackle complex, ambiguous problems Ability to work independently and collaboratively in a fast-paced, global team environment Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps practices is a plus Experience building or maintaining customer service chatbot systems is a plus Familiarity with database technologies (SQL, NoSQL) and cloud data warehouse (BigQuery/Snowflake) Excellent communication and interpersonal skills Fluency in written and spoken English (please send your application in ENGLISH only)Our Tech Stacks includesDeep Learning & ML frameworks & Libraries: PyTorch, Tensorflow, Scikit-learn, OpenCV, TorchServe, TensorflowServingModel serving: Airflow, Torchserve, TFServing, Triton Inference Server, REST APIs, gRPCDeployment: K8sWhat we offer 🎁A meaningful job with an impact on the way people consume fashion and promote sustainabilityThe opportunity to do career-defining work in a fast-growing French-born scale upThe possibility to work as part of a globally diverse team with more than 50 nationalitiesTwo days to help Project - reinforcing your activist journey and volunteer for an associationSignificant investment in your learning and growthCompetitive Compensation And Benefits PackageAs full member of our entrepreneurial project, you will be eligible to free sharesResearch indicates that people from underrepresented backgrounds—including women, people with disabilities, and other marginalized communities—often hesitate to apply for roles unless they meet every single requirement.At Vestiaire Collective, we believe that talent comes in many forms, and we're committed to creating an inclusive environment where everyone can thrive. Your unique perspective could be exactly what our team needs, so we encourage you to apply even if you don't tick every box.Vestiaire Collective is an equal opportunities employer Beware of ScamsVestiaire Collective only contacts candidates via official emails ending in @vestiairecollective.com or no-reply@hire.lever.co . We never use WhatsApp, Telegram, or similar apps for job offers, nor will we ever request payments or banking details.If you receive a suspicious message, please report it to talentacquisition@vestiairecollective.comWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.