Data Scientist

An established, publicly traded global technology powerhouse that has engineered an industry-leading media measurement, optimization, and brand safety platform.

The company's core technology analyzes billions of digital advertisements daily to detect ad fraud, filter out invalid traffic, and identify synthetic or controversial content (such as fake news and brand-unsafe digital environments) in real time.

Processing and parsing data at an astronomical scale, the enterprise leverages advanced Big Data frameworks and highly optimized deep learning classifiers to protect the digital ecosystem.

The company employs over 1,000 professionals globally (with hundreds based in Israel). The R&D center is located in Central Tel Aviv (directly adjacent to the main rail network), operating under a hybrid model of 2 days of remote work per week.

Position Overview

• Data Science Team Leader (70% Hands-on / 30% Management) joining a high-impact core division to lead a team of 3 elite Data Scientists and ML Engineers, reporting directly to a Senior Director.
• Bridging high-level technical management with deep-dive algorithm research, taking ownership of massive multimodal content classification platforms integrated across major global networks (including Meta, TikTok, YouTube, and high-traffic web environments).
• Architecting, training, and deploying advanced Computer Vision (CV), Natural Language Processing (NLP), and Multimodal models designed to run under extremely stringent latency and cost constraints (e.g., within high-throughput, real-time pre-bid ad-decisioning environments).
• Owning the entire model lifecycle end-to-end: from raw telemetry ingestion to active production monitoring.
• Spearheading advanced data labeling strategies, including Active Learning, Auto-labeling, and LLM-driven zero-shot/few-shot annotation pipelines to handle astronomical datasets efficiently.
• Designing next-generation automation frameworks utilizing Embeddings, Vector spaces, and modern Foundation Models.
• Core Domain & Ecosystem- Brand Safety & Ad Verification, High-Scale Data Science Leadership, Multimodal Deep Learning, Real-Time Low-Latency Systems (Pre-bid), Computer Vision & NLP, Data Pipeline Strategy (Active Learning), Python, LLMs & Foundation Models.

Requirements

• 3+ years of direct managerial experience leading Data Science or Machine Learning teams – Mandatory
• 6+ years of hands-on professional experience dedicated to core Machine Learning and Deep Learning development – Mandatory
• Strong, verifiable research and production background in both Computer Vision and Natural Language Processing (NLP) – Mandatory
• Production-grade coding and architectural mastery in Python and its associated ML framework ecosystem (e.g., PyTorch) – Mandatory
• Hands-on experience building and deploying machine learning models that operate within large-scale, low-latency, or high-throughput production systems – Mandatory
• Practical experience or strong conceptual understanding of advanced data strategies (e.g., Auto-labeling, Active Learning, handling highly unbalanced classes) – Strong Advantage
• Experience with modern Generative AI paradigms, including LLM customization, Embeddings, or Foundation Models – Advantage

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