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Staff Data Scientist

Poshmark · US California (Redwood City) - Office

StaffData and MLAll DepartmentsML & Data Engineering TeamPosted 5 months ago

About this role

ABOUT POSHMARK Poshmark is the leading fashion marketplace where style comes alive through discovery, self-expression, and human connection. Powered by a vibrant community of 165 million members, Poshmark brings real people and taste to shopping through a social experience shaped by shared discovery. Buying and selling fashion feels simple, joyful, and personal, while every item tells its own story. Poshmark empowers sellers to grow meaningful businesses, keeps fashion in circulation longer, and gives shoppers access to unique and trusted finds, from everyday pieces to one-of-a-kind vintage and luxury. At Poshmark, we're passionate about harnessing the power of data to drive business impact. As a Lead Data Scientist, you'll tackle complex challenges in personalization, trust & safety, marketing optimization, and product experience. With over 130 million users generating billions of daily events, you'll be at the forefront of data science innovation, developing AI solutions that enhance our platform and delight our community. RESPONSIBILITIES: - Lead end-to-end data science initiatives, from ideation to deployment, delivering measurable business impact through projects such as feed personalization, product recommendation systems, computer vision and GenAI. - Collaborate cross-functionally with ML engineers, product managers, and business stakeholders, to design and deploy high-impact models. - Develop scalable solutions for key areas of product, marketing, operations, and community functions. - Own the entire ML development lifecycle: data exploration, model development, deployment, and performance optimization. - Explore and experiment with emerging AI trends, technologies, and methodologies to keep Poshmark at the cutting edge. MUST-HAVE QUALIFICATIONS: - 5 - 8 years of experience building scalable data science solutions in a big data environment. - Hands-on experience with key machine learning algorithms, including CNNs, Transformers, and Vision Transformers. - Pr

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