Microelectronics Security Data Scientist

The Riverside Research 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 a team of 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 in Dayton, OH and requires each employe to possess and maintain a security clearance. Remote work is not available for this position. Travel is not expected to exceed two to four times a year.

Job 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
• Contributes to proposals for new research in similar and/or related technology areas
• Provide technical mentorship to junior researchers supporting your programs
• Works collaboratively with customers, multi-disciplinary research partners and Riverside Research business, engineering, and technology teams on complex research and development projects

Required Qualifications

• A minimum of 5 years of related experience with a Bachelor's degree, 3 years with a Masters degree, a PhD without experience, or equivalent work experience is typically required for an employee at this level.
• Secret clearance required to start, but must be able 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
• Willing to work in a secure US Government facility
• 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

Desired 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 (e.g., computer engineering, electrical engineering, statistics, computer science, mathematics, physics, or other STEM fields) 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