Applied Data Scientist

Role overview Build and operate recommendation systems that help match people with relevant products and services. This hands-on applied data science role spans the full machine learning lifecycle, from exploratory analysis and modeling through deployment and measurement of business impact.

Responsibilities - Develop, improve, and deploy recommendation models for marketplace use cases. - Run exploratory analyses, prepare data, create features, and build models. - Apply deep learning in production systems, not only offline experiments. - Design experiments and assess results against business outcomes such as revenue, conversion, or retention. - Work with engineering and infrastructure partners to productionize and scale models. - Improve personalization, recommendation quality, and the performance of related business processes.

Requirements - At least five years of experience in production data science. - Hands-on experience taking machine learning models from development into production. - Strong deep learning skills and proficiency in PyTorch or TensorFlow. - Experience with recommendation systems, bidding, dynamic pricing, or a closely related area. - Strong Python and SQL skills, with experience handling substantial data volumes. - Ability to connect model evaluation to business KPIs.

Nice to have - A master’s degree, or a PhD paired with meaningful production experience. - Software engineering experience, especially building data pipelines or production systems.

Benefits and work setup The role is ideally based in Israel; strong candidates in the United States may also be considered.