Data Scientist

A highly profitable, fast-growing Gaming and Data technology startup that engineers an intelligent behavioral loyalty platform utilized by hundreds of thousands of active mobile players globally.

By leveraging advanced Machine Learning and big data analytics, the platform processes massive volumes of tabular user data to deliver hyper-personalized user matches, custom recommendations, and dynamic optimization pricing.

The company scales its close-knit, elite roster with roughly 25 professionals at their central office in Tel Aviv (highly accessible, situated immediately on the train line), operating under a hybrid model providing one day of remote work per week.

Position Overview-

• Lead / Sole Data Scientist acting as the founding, single-focal-point data science professional in the organization, taking end-to-end (E2E) ownership of the company's algorithm architecture.
• Reporting directly to the Chief Technology Officer (CTO), partnering closely to transition existing high-impact data models into a structured, production-scale predictive roadmap.
• Architecting, researching, and deploying mission-critical mathematical models driven by rich behavioral gaming data—encompassing Dynamic Pricing Models, Marketplace Optimization, Recommendation Engines, and Fraud Detection.
• Blending rigorous statistical research with production engineering, deploying Classic Machine Learning pipelines with a heavy focus on tree-based models, complex regressions, and high-volume tabular datasets.
• Core Domain & Ecosystem- Data Science, End-to-End Machine Learning, Classical ML (Tree-based Models, Regressions), Tabular Big Data Analytics, Dynamic Pricing, Recommendation Systems, Marketplace Optimization, and Predictive Analytics.

Requirements-

• Academic Background: B.Sc. (with a strong preference for an M.Sc. or Ph.D.) in a highly quantitative discipline (Computer Science, Data Science, Engineering, Mathematics, or Statistics) from a leading research university – Mandatory
• 5+ years of proven professional experience operating as an End-to-End Data Scientist, transforming raw business data into production-grade ML models – Mandatory
• Deep, first-principles technical mastery of Machine Learning foundations and modern tabular analytics frameworks – Mandatory
• Hands-on expertise building and deploying algorithmic solutions in complex commercial environments, specifically targeting Dynamic Pricing, Marketplace Optimization, Recommendation Engines, or Predictive modeling – Significant Advantage

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