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Director of Data Science

Il y a 2 mois


Paris, Île-de-France Equativ Temps plein
About the Team At Equativ, we are dedicated to creating advertising technologies that enable our clients to achieve their digital business objectives. Our operations depend on highly scalable, distributed, and efficient software systems, managing over 3 million requests per second across 3,000 servers. Our innovation team, located in various cities, comprises over 150 dynamic engineers working in an Agile environment, ready to tackle complex technical challenges. Your Mission As part of the R&D team, we develop a global advertising platform that facilitates the delivery of billions of ads daily through real-time bidding. This system is heavily reliant on machine learning models that enhance cost efficiency, revenue generation, and ad targeting. Our data science teams, based in Paris, focus on crafting advanced deep-learning algorithms to enhance our products. We utilize Google Cloud Platform to train our models with vast amounts of data and deploy them in our own data centers. Leveraging tools like Google Dataflow, Cloud Run, and TensorFlow, our neural networks produce 300,000 predictions per second, each processed in under 2 milliseconds. We tackle a variety of machine learning challenges, including classification, regression, time series analysis, natural language processing, recommendation systems, and reinforcement learning.

Key Responsibilities

Lead and expand our Data Science and Machine Learning engineering teams, focusing on large-scale optimization challenges. Recruit and onboard new talent. Design a high-performance, robust, scalable, and adaptable architecture for model training and production deployment. Identify data science requirements and develop systems, particularly for new projects. Collaborate closely with other engineering teams to enhance and create cutting-edge infrastructure and distributed machine learning services. Stay updated on emerging technology best practices and advocate for their adoption within the organization. Foster a strong engineering culture with an emphasis on quality and excellence.

About You

Possess a product-focused mindset, utilizing the most suitable ML/DS tools to address customer challenges. Hold a Master’s Degree in a technical discipline (Engineering, Computer Science, Applied Mathematics). Have a solid foundation in developing high-performance and responsive data science frameworks. Exhibit a passion for data ecosystems and experience in executing large-scale projects with multiple dependencies. Demonstrate experience in managing a team of Machine Learning Engineers and Data Scientists. Capable of articulating complex concepts to non-technical stakeholders. Proficient in developing Python code in high-load environments. Familiarity with deep learning frameworks. Understanding of data structures and algorithm complexity. Proactive, self-motivated, and organized. Fluent in English, with proficiency in French being a plus.