Data Scientist

A high-growth, well-funded consumer entertainment and streaming media scale-up engineering a next-generation AI-powered platform for short-form digital and mobile video consumption.

Operating at global scale with dozens of employees across international sites and an elite engineering and data core in Israel, the company delivers high-engagement digital content experiences to a rapidly expanding global consumer audience across Web and Mobile.

The organization pairs the high velocity, algorithmic innovation, and equity upside of an early-stage startup with massive concurrent consumer traffic and rich behavioral data streams.

Located in the Central District directly adjacent to a major train hub, operating on a flexible hybrid model with two days working from home.

Role Description-

• Serving as a Senior Applied Data Scientist (Personalization & Recommendations), joining the foundational Data Science squad and reporting directly to the CTO, with end-to-end ownership over transition from heuristics/rule-based mechanisms to advanced ML-driven personalization engines.
• Architecting, developing, and deploying production-grade Recommendation, Ranking, and Personalization systems governing the complete user lifecycle—including dynamic feed discovery, push notification optimization, contextual promotions, and conversion triggers.
• Leading the full ML lifecycle: from exploratory behavioral data analysis and feature engineering to model design, offline evaluation, online A/B experimentation, deployment, and ongoing production monitoring.
• Developing predictive behavioral models including User Lifetime Value (Predicted LTV), churn mitigation, propensity scoring, and dynamic engagement modeling.
• Implementing Deep Learning (DL) architectures, sequential/time-series algorithms, and Causal Inference methodologies to quantify algorithmic uplift and continuous user engagement.
• Partnering cross-functionally with Product, Core Engineering, and Marketing/Content stakeholders to turn algorithmic insights into core product features.

Requirements-

• Bachelor’s degree (B.Sc. / B.A.) or higher in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field – Mandatory
• 5+ years of dedicated professional hands-on experience as a Data Scientist – Mandatory
• Proven, hands-on production track record designing and deploying Recommendation and/or Personalization systems (preferably from content recommendation, ad-tech, or large-scale digital consumer platforms) – Mandatory
• Deep practical expertise with Deep Learning (DL) architectures applied to ranking, classification, or recommendation – Mandatory
• Strong practical experience working with Time-Series / Sequential behavioral data and temporal feature modeling – Mandatory
• Proven background in A/B Testing, online experimentation design, and statistical validation / Causal Inference – Mandatory
• High degree of end-to-end technical independence (from raw data exploration to production-ready models) and fluent communication skills in English (written and verbal) – Mandatory