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The Applied AI team at Datadog designs and builds algorithmically driven features across the platform, with a focus on streaming data analysis including anomaly detection, error outliers, and faulty deployment analysis. As a Senior Applied Scientist, you will design and build machine learning models and algorithms that power production features within the Datadog observability platform.
You will research and benchmark relevant algorithms to identify the best solutions for specific use cases, leveraging machine learning and statistical techniques to create scalable product features. Your responsibilities include developing, deploying, and monitoring new and existing features in production, as well as maintaining the models, services, and infrastructure owned by your team. You'll participate in the team's journal club by reading and presenting the latest academic research papers, explore and analyze high-volume data flowing through Datadog systems, and contribute to the team's on-call rotation.
You will work closely with engineering and product partners to explore, build, scale, and deliver features incubated within the Applied AI team. The role emphasizes code simplicity, performance, and the ability to explain complex algorithms to non-technical audiences. You'll have the opportunity to collaborate with colleagues across Datadog offices in New York City and Paris, attend and present at conferences, and participate in mentorship and community guild programs.
Required qualifications include a BS, MS, or PhD in Computer Science, Engineering, Machine Learning, or a related scientific field (or equivalent experience). You should have hands-on experience with high-scale systems and datasets, including building models, applying machine learning to real business problems, and writing production data pipelines. Strong communication skills and genuine excitement about working on user-facing products are essential.
