🇳🇱 Amsterdam, Netherlands · 2w ago
Senior Data Scientist
Waving
LinkedInseniorEnglish-friendly
Role summaryWaving is looking for a Data Scientist who is meticulous, organized, and precise in handling data. You will work hands-on with real-world sensing data, build and validate detection models, and help translate experiments into reliable performance in operational environments.The ideal candidate is highly independent, learns quickly, and can take ownership of tasks end-to-end, from data exploration and tooling to model development and evaluation.ResponsibilitiesAnalyze and clean large-scale sensing datasets, create repeatable pipelines and clear documentationDevelop, test, and improve models for detection and classificationDesign experiments and evaluation methodologies, define metrics, and report results clearlyWork closely with engineering to deploy models and iterate based on field performanceBuild lightweight tooling to visualize data, debug edge cases, and accelerate iterationMandatory RequirementsAt least a bachelor’s degree in Electrical Engineering or Physics.5+ years professional experience with Python5+ years professional experience using machine learning and data analysis tools.AdvantagesFamiliarity with signal processing, wireless communication, or RF signals.Experience working in a cloud environment.Nice to haveSignal processing experience (time-series, filtering, FFT, feature extraction)Familiarity with wireless communication or RF sensing conceptsExperience working with cloud environmentsWaving creates an invisible security layer that detects human presence indoors and outdoors, even through walls and around corners. Built for critical infrastructure and high-security sites, our technology reduces blind spots and false alarms, strengthens patrol and camera effectiveness, and integrates seamlessly into existing control rooms, all while preserving complete privacy. Tested by Schiphol Airport Security and government security agencies.Sourced from LinkedIn. Relocantly aggregates public job postings; apply on the original site.