Microelectronics Security Data Scientist

Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country’s most challenging technical problems. All opportunities require U.S. Citizenship.

About the role

The Engineering and Support Solutions (ESS) directorate conducts Research and Development (R&D) of cyber-physical attacks against embedded systems. As a Microelectronics Security Data Scientist, you will collaborate with a multi-disciplinary team of research engineers and scientists on a wide range of microelectronics research projects. You will work directly with hardware security research subject matter experts (SME), the senior Principal Investigator, Technical Lead, and Program Manager to support various project-specific research projects developing solutions to complex, open-ended hardware security problems. The position is based in Dayton, OH and requires possession and maintenance of a security clearance. Remote work is not available. Travel is not expected to exceed two to four times a year.

Responsibilities

• Conduct research in the application of data science, including deep learning and complex statistical data analysis, for problems within microelectronic hardware security
• Perform all aspects of the data science lifecycle: gather requirements from non-data science technical staff, propose technical approaches, pre-process data, perform exploratory data analysis, model the data, critically evaluate performance of the model, and present findings
• Develop whitepapers and presentations to communicate research findings
• Contribute to proposals for new research in similar and/or related technology areas
• Provide technical mentorship to junior researchers supporting your programs
• Work collaboratively with customers, multi-disciplinary research partners, and Riverside Research business, engineering, and technology teams on complex research and development projects

Requirements

• A minimum of 5 years of related experience with a Bachelor's degree, 3 years with a Master's degree, a PhD without experience, or equivalent work experience
• Secret clearance required to start; must be able to obtain Top Secret security clearance and all required program access approvals
• Expertise with machine learning in one or more of the following: Unsupervised Learning, Bayesian classifiers, Regression, Random Forests, Deep Learning, Graph Neural Networks, Belief Propagation, Statistical Inference, Dimensionality Reduction
• Proficient in Python and popular data science libraries (NumPy, Scikit-Learn, Matplotlib, etc.)
• Demonstrated experience across the full data science lifecycle, for classification/regression, clustering, basic text analytics, image recognition, or other related applications
• Experience presenting technical material to both technical and non-technical audiences
• Ability to manage timelines, product delivery, and product quality for research projects
• Interest in solving open-ended research challenges
• Willing to travel 2-4 times per year
• Bachelor’s Degree in a quantitative discipline (e.g., computer engineering, electrical engineering, statistics, computer science, mathematics, physics, or other STEM fields) and 5 years' experience, or Master’s Degree in a related discipline and 3 years' experience, or a PhD in a related discipline

Qualifications

• Active DoD Top Secret (TS) or equivalent US Government security clearance
• Experience with TensorFlow, PyTorch, or similar Deep Learning framework
• Experience with parallel and distributed processing of large data sets across multiple GPUs
• Experience with data transformations such as Principal Component Analysis (PCA)
• Experience using revision control software
• Experience leading a small technical team on research projects
• Understanding of information theory and its application to cryptographic algorithms
• Understanding of signal processing is highly desired
• Bachelor’s Degree in a quantitative discipline and 8 years' experience, or Master’s Degree in a related discipline and 3 years' experience, or 3 years' practical experience with a PhD in a related discipline

Pay

This represents the typical compensation range for this position based on experience, location, and other factors.