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