Senior Data Scientist (Growth)

Join our team as a Data Scientist, Growth. In this high-exposure role, you will own the machine-driven decision engines and automated bidding infrastructure guiding a massive global performance marketing spend across 40+ business units. You will have the autonomy to build end-to-end production models and write the core software fueling our growth engine. This position offers a direct line to executive leadership and a clear, measurable view of your impact on our top and bottom lines.

• Concevoir, construire et mettre en production des modèles d'apprentissage automatique autonomes et des pipelines de données de production qui automatisent la logique opérationnelle et l'efficacité des dépenses.
• Gérer les intégrations de la plateforme publicitaire, gérer l'automatisation des enchères et optimiser les flux de travail complexes de la technologie marketing.
• Collaborer de manière transversale avec les équipes marketing, produit et science des données tout en maintenant un accès de haute visibilité à la direction exécutive.
• Proven background as a Data Scientist, Machine Learning Engineer, or ML Researcher with hands-on experience independently pushing machine learning models into a live production environment
• 2+ years of technical experience, including at least 1 year of corporate/industry experience
• Excellent collaboration and communication skills to work effectively with cross-functional partners and leadership teams
• Ability to dig deep into complex systems within a fast-paced, high-leverage entrepreneurial environment without a massive supporting infrastructure
• Deep analytical and problem-solving strengths with a demonstrated history of working independently on loosely defined optimization and statistical problems
• Technical proficiency in Python and SQL
• Direct domain experience in ad tech infrastructure, automated campaign management, digital advertising, performance marketing tech, programmatic bidding optimization or automated investment platforms
• Experience working within a direct-to-consumer, retail, or e-commerce environment, particularly owning data pipelines for real-time bid pricing or user attribution platforms
• Practical engineering exposure to large language models (such as Claude) and working with vector spaces