Data Scientist

Were looking for an experienced, rigorous Data Scientist to join our monetization data team in Tel Aviv. Youll lead dynamic price-floor optimization strategies for programmatic display advertising across our global inventory, build models and experiments that determine which on-page experiences we show each user, and develop strategies to maximize user lifetime value while strengthening engagement and retention. Youll also shape and manage the roadmap for our internal experimentation platform, enabling rigorous testing across the business.

This is publisher-side data science, focused on our own audiences and those of our partners. The bar that matters most here is measurement, proving credibly that a change actually moved revenue before it ships.Responsibilities:Design and build models for supply-side monetization optimization, user lifetime-value, retention, and ARPU predictions, while measuring revenue impact.Analyze large-scale event data and maintain metric foundations.Partner with cross-functional teams to deploy models into production.Communicate findings and business impact to stakeholders.Provide technical leadership and mentorship.Monitor industry trends in programmatic advertising and ad-tech.Requirements: Requirements:4 years in data science / ML applied to a data-heavy, revenue-facing domain - ad-tech, programmatic monetization, marketplaces, pricing, or a comparable real-money optimization problem.Strong causal-inference and experimentation skills. This is the core of the role.Fluent SQL on large event datasets and hands-on Python for modeling and analysis.Solid grounding in the relevant ML families - regression, tree-based models, online optimization / multi-armed & contextual bandits, and classification/segmentation.In-depth understanding of programmatic advertising from the supply side - RTB, auction mechanics, header bidding, price floors, and how publisher yield is actually made.Ability to design experiments that measure model effectiveness in production, and to own the definitions (metrics, identity, attribution) they rest on.Experience integrating models into production systems with engineering, in a fast, iterative environment.Proven ability to architect and scale models processing high-volume, real-time event streams.Excellent communication - able to turn a complex monetization result into a clear recommendation a non-technical stakeholder can decide on.Fluent English, written and spoken.Advantageous:Hands-on experience with publisher-side monetization/yield optimization, header bidding, or price-floor / seller-side auction optimization specifically.Familiarity with the Prebid stack (client & server).Subscription/membership/LTV modeling - retention, churn, and balancing recurring revenue against ad revenue.Working knowledge of GA4 / behavioral analytics and first-party identity resolution.Prior experience mentoring or leading a small data-science team.This position is open to all candidates.