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Amsterdam
24 Apr 2026
Senior Applied Scientist - Observability logo

Senior Applied Scientist - Observability

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Amsterdam
24 Apr 2026
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Senior Applied Scientist - Observability

We are looking for a Senior Applied Scientist to build a real-time observability platform for customer experience. You will design anomaly detection, statistical monitoring, and data infrastructure to improve service quality. Requires 6+ years of experience and expertise in machine learning, causal inference, and time-series analysis.

On-siteFull-timeSeniorAnomaly DetectionTime-series Analysis

Senior Applied Scientist - Observability

We are looking for a Senior Applied Scientist to build a real-time observability platform for customer experience. You will design anomaly detection, statistical monitoring, and data infrastructure to improve service quality. Requires 6+ years of experience and expertise in machine learning, causal inference, and time-series analysis.

Apply
On-siteFull-timeSeniorAnomaly Detection

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

On-site

Experience Required

6 years

Employment Type

Full-time

Experience Level

Senior

Core Qualifications

Technical (Must-have)
anomaly detectiontime-series analysiscausal inferenceA/B testingPythonSQLPySparkFlink SQLmachine learningstatistical monitoring
Soft Skills
communicationthought leadershipownershipcross-functional collaborationproblem solvingcritical thinking
Tools (Must-have)
KafkaSparkOLAP stores

Preferred Qualifications

Technical (Nice-to-have)
event correlationchange attributionobservabilityexperimentation platformsreliability monitoring

Key Responsibilities

  • •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.
  • •Contribute to intelligent incident response workflows: auto-triage, root-cause hints, auto-mitigation actions.
  • •Develop statistical monitoring approaches for code deployment safety and feature rollout safety.
  • •Support safe and fast product releases by adjusting deployment soak times or rollout speed based on statistical significance.
  • •Partner with Engineering on building data infrastructure producing analytics-ready datasets.
  • •Define best practices in instrumentation and metric definitions for incident detection.
  • •Contribute to monitoring coverage assisted observability and monitoring.
  • •Define success metrics for incident detection systems and create evaluation harnesses.
  • •Communicate results clearly to technical and non-technical stakeholders; drive alignment on tradeoffs, OKRs and roadmap.
Senior Applied ScientistObservabilityAnomaly DetectionTime-seriesCausal InferenceMachine LearningPythonSQLAmsterdamFull-time
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