Derive new signals from high-throughput, real-time data streams, inferring complex physical and
Build, evaluate, and iterate on models across diverse modalities, including dense time-series
Design evaluation for problems with little or no labeled ground truth, using weak supervision, and
Partner with backend and platform engineers to take models from offline analysis into production
Work directly with aviation subject-matter experts to turn operational knowledge into features

🎯 Requirements

BS/MS/PhD degree in Computer Science, Statistics, Applied Mathematics, Operations Research
2+ years of applied data science or machine learning experience, including models that have run in
Strong Python and strong SQL over large analytical datasets.
Depth in time-series and sequence modeling.
Experience working with sparse, incomplete, or unlabeled data — weak supervision, programmatic
Experience designing data validation and drift detection for continuously arriving data.

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