Head of Data Science

About the team At Equativ, we’re on a mission to develop advertising technologies that empower our customers to reach their digital business goals. This means that we rely on massively scalable, widely distributed, highly available, and efficient software systems; the platform deals with over 3 millions requests per second managed by 3,000 servers.Our innovation team based in Paris, Nantes, Limoges, Krakow and Berlin is composed of 150+ straightforward and energetic engineers working in an Agile environment and ready to tackle the most complex technical challenges. Your mission Within the R&D team, we build a global advertising platform allowing the delivery ofbillions of ads daily using real time bidding. This pipeline heavily relies on machine learning models that allow lower costs, higher revenues, better targeted ads and more. Our data-science teams are based in Paris and are responsible for designing awesome deep-learning algorithms to make our products smarter. We train our models in Google Cloud Platform with billions of logs, and serve them in our own data centers. We use Google Dataflow, Cloud Run and Tensorflow. Our neural networks generate 300k predictions per second, each prediction processed in less than 2 ms. We work on all kinds of machine learning problems (classification / regressions, time series, NLP, recommendation, reinforcement learning...).As head of data Science, you will be responsible for the overall design, availability and performance of both the learning pipeline and the use of models in the delivery engines. You will manage a team of 10+ Data Scientists and Machine Learning Engineers and closely interact with Business, Product, Data Engineering, Back End teams …

What you'll do ️

• Drive and grow our Data Science and ML engineering teams, with a passion for large-scale optimization challenges
• Design a high performance, robust, scalable and flexible architecture to train models and run them in production
• Identify data science needs and design systems especially when launching new projects
• Work closely with other engineering teams to refine and develop cutting-edge infrastructure and distributed machine learning services
• Keep on top of the emerging technology best practices and champion these within the organization
• Contribute to promoting a strong engineering culture and passion for quality and things well done

About you

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