The Advanced Analytics Team applies expertise in machine learning, large-scale computational architectures, data visualization, and simulation to solve hard research challenges in high impact areas including cybersecurity, biological systems, and distributed sensor platforms. We’ve built automated malware detection systems, deep learning models that can semantically label source code, prototypes to visualize graphs with millions of nodes, and a distributed framework that can process and store sensor network streams on the scale of 100 MB/s.
Our team values creativity, initiative, collaboration, and diversity. We strive for a fun and collegial atmosphere that encourages intellectual crosspollination and professional growth. In short, we’re passionate aboutempowering our customer’s missions and enjoy working together at the leading edge of technology!
- Experience applying machine learning to challenging problems (multiclass classification, clustering, etc.).
- Experience with digital signal processing techniques (matched filters, spectral estimation, wavelets, noise reduction, etc.) or with applying machine learning to audio.
- Demonstrable programming experience with Python, C/C++, Java, or similar language, and knowledge of computer science fundamentals.
- Comfortable using mathematics, statistics, or visualization to model and analyze complex problems and communicate research results.
- Ability to work collaboratively on multidisciplinary teams.
- BS degree in Computer Science, Electrical Engineering, Applied Math, or related technical field, or equivalent practical experience.
- US citizenship.
Nice to Have:
2+ years of relevant practical experience or an MS degree in Electrical Engineering, Computer Science, Applied Math, or related technical field. Familiarity with software development tools and platforms (Git, Linux, etc.). Familiarity with data science tools (Keras, Sklearn, PyTorch, etc.). Experience with deep neural networks, CNNs, or embedding techniques.