Вакансии: Данные

Build production data and machine-learning pipelines that classify, normalize, structure, and match product data across a catalog of more than a billion records. Work with LLMs and other ML methods, scale solutions on cloud infrastructure, and collaborate with Product and R&D teams.

A mobile gaming company is hiring a data scientist to develop and deploy models that shape player experiences and improve retention and monetization. The role spans problem definition, data and modeling, backend integration, and impact measurement.

Lead and mentor a team of data scientists building AI solutions for digital pathology, oncology, and drug development. Combine technical direction and team leadership with hands-on machine learning work. The role is based in the Tel Aviv office four days per week, with a fixed work-from-home day onT

Develop real-time predictive models and simulations using historical sports data to produce forecasts and betting insights.

Own product analytics for classification and brand safety, supporting data-driven decisions, analytics engineering, and AI-assisted reporting workflows.

Lead research and development of deep learning solutions for semiconductor metrology challenges within a technology research group.

Join an AI delivery team building end-to-end AI solutions for enterprise clients. Work primarily on Generative AI, including RAG pipelines and LLM systems, as well as classical machine learning and data science. The full-time role is on-site in Lod and requires security clearance.

Seeking a specialist to develop and maintain the mathematical model and economy for a CS2 skin case-opening platform. The work includes the initial model and continued development of new mechanics and balance.

Join a cybersecurity team developing and deploying machine learning and LLM capabilities to address complex security challenges. Work with data scientists, engineers, security researchers, and product managers from research and experimentation through production.

Own applied machine learning for recommendations and personalization, from behavioral data and model adaptation through production deployment and impact measurement.