Senior Applied Scientist

Senior Applied Scientist Department: Data Science Team: Data Scientist Location: Amsterdam, Netherlands Type: Full-Time **About the Role** We are looking for a Senior Applied Scientist with a passion for building software solutions where customer experiences take centre stage and products are built with service quality at heart. We are building a real-time data platform to enable customer experience observability and analytics at scale: key ingredients to ensure we deliver best-in-class experiences for our users. The platform helps detect and respond to degradations in customer experience, supports safe code deployments and fast feature rollouts through real-time monitoring, and powers deeper analytics that inform product improvements, enabling both reactive and proactive service quality processes. This is an outstanding opportunity for an applied scientist with a collaborative spirit to the core, who will work with the engineering team to drive an ambitious observability platform. It’s a high-impact role where you will collaborate on challenges across domains and functions, spanning time-series anomaly detection, statistical monitoring and guardrails, and the data foundations needed to make customer experience measurable and actionable. If you have the technical chops, we invite you to join us to solve tough large-scale data challenges and raise the bar of service quality. **What You Will Do** **Incident Detection & Mitigation** - Design and improve state-of-the-art anomaly detection and alerting for multivariate time series metrics. - Build methods to reduce incident impact, such as by shortening incident time-to-detection and time-to-resolution while reducing alert fatigue (deduplication, correlation, grouping, etc). - Contribute to intelligent incident response workflows: auto-triage to right team, suspected root-cause hints, auto-mitigation actions as well as agentic mitigation flows (supporting on-call Engineers in debugging and mitigating). **Rollout Safety & Speed (Experimentation & Monitoring)** - Develop statistical monitoring approaches for code deployment safety