Data Scientist ML Engineer — Water Infrastructure, REMOTE GDANSK

  • Strong data science fundamentals (modeling, validation, interpretation) and solid data engineering skills (pipelines, APIs, data quality)

  • Python — must have

  • Comfortable with ambiguous, messy real-world data

  • Nice to have: Go, TypeScript

  • Bonus: experience in water/utilities, environmental, or industrial IoT domains

  • Bonus: time-series, anomaly detection
We build ML systems that help water utilities and infrastructure operators predict and prevent failures — sewer overflows, flood risk, infrastructure breakdowns. Real-world impact, real sensor data, real consequences when the model gets it wrong. Small, distributed team across Poland and Canada. ,[Own the full pipeline-to-model workflow: from raw, messy sensor/telemetry data to production-ready predictive models, Build and maintain the data pipelines your own models depend on, Work directly with utility operators and engineers — your models inform real operational decisions, Shape our approach to anomaly detection, time-series forecasting, and physics-informed ML, Collaborate across a distributed team (Poland + Canada)] Requirements: Python, SQL, Machine learning, Kubernetes Tools: Confluence, GitHub, GIT, Agile, Scrum. Additionally: Training budget, Small teams, Flat structure, International projects, Free coffee, Bike parking, Shower, Free parking, No dress code.
Data publikacji: 2026-06-25
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