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Applied Scientist, Leo Security

Amazon· Leo Space Security
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Hybrid (Arlington, VA), Hybrid (Herndon, VA), Hybrid (Bellevue, WA)$142.8k - $193.2kFull-timePosted yesterday

About the role

Applied Scientist role in the Leo Space Security engineering and R&D team. Focus on building statistical and behavioral models to defend a global satellite constellation’s manufacturing lines, launch sites, and ground infrastructure. Production-grade research with privacy-preserving data representations and deployment into security systems.

Responsibilities

  • Build behavioral and statistical models that baseline normal activity across heterogeneous security telemetry, including specialized industrial-control and factory-floor data sources, so detections extend to new environments with low false-positive rates.
  • Design privacy-preserving representations of sensitive security data, and verify that models and detections tuned against them remain accurate against the real data — turning data-protection guarantees into measurable, provable properties rather than assertions.
  • Define the methodology and own the analysis for difficult, loosely defined problems: gather complex data across domains, select the right techniques from a range of data science methods, and justify your approach with evidence.
  • Develop the metrics and evaluation frameworks that measure model and detection performance against threat actor behavior before a model is trusted in production.
  • Contribute to the team's neurosymbolic reasoning platform, adapting state-of-the-art techniques from the literature and shipping components at production quality.
  • Document your work with the rigor of a peer-reviewed publication, and communicate results clearly to both scientific and security-operations audiences.

Qualifications

  • 3+ years of building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience with statistical modeling and analysis of large, heterogeneous datasets, including anomaly detection, time-series analysis, or behavioral baselining
  • Fluency in Python; experience with a systems language such as Rust or C++ is a plus
  • Experience with popular deep learning frameworks (e.g., PyTorch, TensorFlow)

Skills

Required:Statistical modelingPythonDeep learning frameworks
Nice to have:Systems programming (Rust/C++)
Last updated Oct 25, 2026. Interested? Apply on the company site.

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