Data Science Team Lead

A highly successful, profitable technology company operating in the AdTech ecosystem, developing an intelligent, automated platform that optimizes mobile advertising campaigns in real time.

Operating as a lean, data-first organization, the firm provides an elite engineering playground where data science directly dictates the core product strategy and commercial revenue generation.

The company's corporate offices are located in Tel Aviv (exceptionally accessible, situated directly on a primary train line) and operate on a hybrid model allowing for two days of remote work per week.

Position Overview-

• Data Science Team Lead stepping into a pivotal leadership role, commanding an organic squad of data scientists who directly own and scale the company's core predictive engine.
• Balancing strong strategic people management with high-level technical guidance, driving the deployment of highly predictive machine learning models and classical ML architectures into live production.
• Overseeing the entire data lifecycle—from conceptual mathematical formulations and feature engineering through to scalable production deployment.
• Collaborating closely with cross-functional R&D, Data Engineering, and Product divisions to turn complex business objectives into production-grade algorithmic behaviors.

Requirements-

• M.Sc. or Ph.D. in Computer Science, Mathematics, Physics, Engineering, Statistics, or a highly quantitative discipline (Mandatory).
• 6 years of proven professional experience as a Data Scientist inside product-centric organizations (Mandatory).
• 1 years of direct technical leadership experience (such as Team Lead, Tech Lead, or Principal Project Lead) (Mandatory).
• Proven track record of driving complex Data Science initiatives from concept to production deployment (Mandatory).
• Comprehensive programming and engineering mastery utilizing Python alongside standard data science toolchains (Mandatory).
• Strong analytical problem-solving abilities with the capability to match mathematical approaches to specific business challenges.
• Prior practical experience engineering or mining insights from large-scale datasets is a highly advantageous asset.