Job Purpose/Summary

Work with our team of engineers, scientists and human factors professionals to develop machine learning and other algorithmic data capabilities for applications in cybersecurity, space, and telecommunications. This individual contributor role will involve hands-on work developing solutions to real-world problems using neural networks and other algorithms. Developed solutions are actively being productionized to support ongoing space operations and other crucial infrastructure and security needs.

Duties and Responsibilities

• Develop and evaluate machine learning solutions to interdisciplinary problems in cybersecurity and telecommunications, working with structured (time series, tabular) and unstructured (text, 3D) data.
• Collaboratively develop data collection plans, designing experiments to ensure quality and usefulness of data.
• Work with human factors specialists, and data/full stack engineers to define system requirements, review developed code, and support translating statistical concepts to coworkers.
• Support documentation of analysis results for semi-technical stakeholders.
• Occasionally support technical interactions with collaborators, including defining technical requirements for external data collections, and reviewing technical work.

Qualifications

Minimum:

• Graduate formal education in natural sciences, mathematics, economics, statistics, psychology, or other quantitative field, or mix of formal education and experience.
• 2 years’ professional experience with an open-source data science stack (e.g., pandas, numpy, pytorch, keras, tensorflow, pymc3).
• 2 years’ professional experience working with real-world, complex datasets.
• Experience communicating technical results to semi-technical audiences.

Preferred:

• Exposure to a product-driven machine learning organization with deployed customer-facing capabilities.
• Exposure to a big data environment, including tools for clustered computing (e.g., Spark, Dask, streaming) and large-scale data storage.
• Experience with RF/telecommunications physics, cybersecurity, or space operations.
• Experience with software defined radio applications

Working conditions

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Physical requirements

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Direct reports

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