Senior Data Scientist, Teads

• Strong communication skills, working collaboratively with the team, able to teach concepts, and communicate clearly to a wide audience complicated topics
• Strong problem solving skills, and deducing from specific problems wider range products
• True scientist skills: fast learner, curious, sense of details, rigourous
• Experience in Statistics (i.e. statistical analysis, regression analysis, …) and/or Artificial Intelligence (i.e. Data Mining, Machine Learning, …)
• An appetite for Data Science applied to high-volumetry, low-latency topics
• Ability to read scientific articles, to analyze critically, and to implement as appropriate
• Good programming abilities
• You are very mindful about your application architecture, performance, testing and maintainability and its overall quality

Desirable

• Working in a very high-traffic environment (1.9 billion users per month, 100 billion events per day) with low latency and high availability constraints (2 million requests per second, responses in less than 150 milliseconds)
• Rich and diverse tech stack and system architecture to optimize for performance, scalability, resiliency, and cost efficiency. We use mostly Scala and TypeScript, among others
• Management of large datasets with milliseconds order of magnitude access time, to compute in a near real-time complex auction resolution algorithm (18 million predictions per second)
• Build efficient and easy-to-use web products used by thousands of users working for the world's most premium publishers, advertisers, and agencies
• A fast-changing environment where we continuously collaborate with Product teams and constantly adapt our Cloud infrastructure for new features and Products
• Bring a wide diversity of profiles to the same level of quality and knowledge
• Improve existing algorithms & tools allowing to explore and analyze more and more data and provide accurate feedback on the Teads activities
• Develop new algorithms & new approaches to provide accurate predictions and drive new products by providing business insights
• Implement your algorithms and models end to end
• Collaborate with a variety of teams to develop services from design to production
• Make sure the software is in good hands by writing, running and automating tests (unit, functional, load...)
• Keep up to date with the latests Machine Learning technologies to make sure we always use the best class algorithms according to the context