
11 - 50 employees
🤖 Artificial Intelligence
🛍️ eCommerce
👗 Fashion
Artificial Intelligence • eCommerce • Fashion
Bold Metrics Inc. is a San Francisco-based company that offers advanced AI-powered SaaS solutions to optimize apparel fit and sizing. Their platform uses digital twin technology to recommend precise sizes, thereby enhancing customer satisfaction, reducing returns, and boosting conversion rates in the eCommerce space. Bold Metrics empowers brands to leverage in-depth body data, providing a contactless and tailored user experience that adapitates from online to in-store shopping. The company is trusted by renowned fashion brands and helps them seamlessly integrate its solutions for improving fit and enhancing personalization.
🕒 July 30, 2025
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11 - 50 employees
🤖 Artificial Intelligence
🛍️ eCommerce
👗 Fashion
Artificial Intelligence • eCommerce • Fashion
Bold Metrics Inc. is a San Francisco-based company that offers advanced AI-powered SaaS solutions to optimize apparel fit and sizing. Their platform uses digital twin technology to recommend precise sizes, thereby enhancing customer satisfaction, reducing returns, and boosting conversion rates in the eCommerce space. Bold Metrics empowers brands to leverage in-depth body data, providing a contactless and tailored user experience that adapitates from online to in-store shopping. The company is trusted by renowned fashion brands and helps them seamlessly integrate its solutions for improving fit and enhancing personalization.
• Please submit your resume in English. Applications in other languages may not be considered. • Bold Metrics is the leading fit and sizing solution on the market today for the world’s top retailers and brands. We are a venture-backed startup that is making a big impact on the environment, forever changing the landscape of eCommerce. We are a remote-first company that is full of inspiring and friendly people. • We are currently searching for a Data Scientist to join our fast-growing team. This position is for someone located in São Paulo, Brazil who is able to come into the office in-person at least once weekly. In this position you will have the opportunity to work with some of our biggest projects within the retail industry. • You are a humble, passionate, and experienced engineer that is looking for a collaborative and analytical Data Scientist role to support the execution of our product deliveries and machine learning pipeline. This comprises validating the data flow from data sources, analyzing patterns and trends in the data, and facilitating machine learning updates to the system. • As our Data Scientist, you are an extremely detail oriented, out-of-the-box problem solver with a commitment to doing high-quality work. You will work closely with the Engineering and Data Teams, alongside Customer Success teams to support the flow of data collection and machine learning initiatives to ultimately drive customer success. • Lead strategic decision-making for user growth and product innovation by utilizing the full range of data science tools, including analytics, experimentation, forecasting, and machine learning, to enhance the entire consumer experience. • Develop and deploy machine learning models and causal inference techniques at scale, from concept to measurable business impact. • Design and oversee experiments and analyses to evaluate product performance and drive continuous improvements. • Build and maintain automated, scalable data pipelines to support reporting, data visualization, analytics, and machine learning for internal products and solutions. • Lead the design and management of comprehensive machine learning platforms, ensuring robust model development and deployment processes.
• BSc or MSc in Mathematics, Computer Science, Engineering or related field. • Over 3 years of hands-on experience in Data Science, Machine Learning, and Deep Learning. • +4 years of demonstrated high proficiency in Python and SQL. • Practical expertise in A/B testing and causal inference. • Extensive experience with AWS cloud technologies. • Proficient in MLOps practices, including model deployment and monitoring. • Experience with Docker for containerization and Git for version control.
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