Aug 08, 2022

Applied Research Mathematician / Multimedia Forensics and Authentication - Experienced Level (MD)

  • National Security Agency
  • Fort Meade, MD, USA

Job Description

- Analyze problems and determine procedures required to solve technical problems; - Create computer algorithms, data models, and protocols; - Identify new applications of known techniques; - Analyze data, algorithms, and communication protocols using mathematical/statistical methods; - Develop and apply mathematical or computational methods and lines of reasoning; - Design, develop and debug software solutions; - Create and maintain documentation on research processes, analyses and/or the results; - Write logical and accurate technical reports to communicate ideas across the enterprise; - Effectively instruct, mentor, and support the professional development of colleagues in the areas of technical expertise.

NSA's Mathematics Research Group conducts world-class mathematical research with the objective of developing new and innovative techniques and technologies to support our Signals Intelligence and Cybersecurity missions, as well as the broader Intelligence Community (IC). We are actively seeking mathematicians to join our Statistics and Machine Learning Research Office. The office focuses on fundamental mathematics research in the applications of machine learning and statistical analysis, as well as a wide range of other technical areas to include cryptography, vulnerability research, machine learning security, network defense, digital forensics, and graph algorithms. In particular, Statistics and Machine Learning Research is seeking candidates with experience in multimedia forensics and authentication (MFA). MFA is the process of analyzing digital files (e.g., audio, video, image, and text) for signs of alteration, either in the form of the content, metadata, or file container. We are looking for individuals who have the skills to develop algorithms to aid in this detection process, and the desire to research and development new features and explainable forensic techniques using statistics and machine learning. The ideal candidate has experience in the MFA realm, proficiency with digital media, data science/machine learning skills, and a willingness to explore ideas through extensive research and development. We are looking for a team focused researcher, willing to collaborate and share knowledge.

The qualifications listed are the minimum acceptable to be considered for the position. Salary offers are based on candidates' education level and years of experience relevant to the position and also take into account information provided by the hiring manager/organization regarding the work level for the position. Degree in Mathematics, Physics, Engineering, or Computer Science is preferred. Degree must include 2 years (which equates to approximately 24 credit hours) of advanced mathematics. Relevant experience must be in the design, development, use, and evaluation of mathematics models, methods, and/or techniques (e.g., algorithm development) to study issues and solve problems. Senior Level (Grade: 13-14) Entry is with a Bachelor's degree plus 6 years of relevant experience, or a Master's degree plus 4 years of relevant experience, or a Doctoral degree plus 2 years of relevant experience. Expert Level (Grade: 15) Entry is with a Bachelor's degree plus 9 years of relevant experience, or a Master's degree plus 7 years of relevant experience, or a Doctoral degree plus 5 years of experience.

The ideal candidate is someone with excellent problem-solving, communication, and interpersonal skills, who possesses a range of knowledge and experience with: - Applying principles and methods of linear algebra (e.g., vector spaces, matrices, matrix manipulations) to solve complex problems; - Applying the mathematical principles, combinatorial methods or elicitation techniques to determine or calculate the likelihood of outcomes; - Quantifying the likelihood of an event's occurrence; - The scientific principles, methods, and processes used to conduct research studies (e.g., study design, data collection and analysis, and reporting results); - Concepts and procedures for applying algorithm design techniques (e.g., data structures, dynamic programming, backtracking, heuristics, and modeling) to design correct, efficient, and implementable algorithms for real-world problems; - Debugging and testing software programs; - Using best programming practices (e.g., appropriate coding standards, algorithm efficiencies, coding documentation); - Using principles, techniques, procedures, and tools that facilitate the development of software applications; - Using software and computer languages and skills (e.g., writing code, debugging/testing programs, fixing syntax, correcting logic errors, using abstract data types) to develop programs that meet technical requirements - Applying data-analytic techniques to analyze, visualize, and summarize sample data from populations; - Drawing inferences regarding populations based on results from sample data. Qualified applicants will have a strong technical background in a computational science discipline (e.g., Mathematics, Statistics, Data or Computer Science) and research experience in mathematical analysis of large data sets. Experience in operational areas is a plus. Exceptional candidates will have experience applying machine learning methods, including but not limited to a subset of network-based learning (e.g., deep learning, GANs), reinforcement learning, ensemble methods, and large scale graph analytics. Significant programming experience, especially working with large data sets (e.g., Python, Tensorflow, R, Java, C/C++, and/or other data processing frameworks) is preferred.

This is a full-time position. Work Schedule: Monday - Friday, with basic 8hr/day work requirements between 0600 to 1800 (flexible). On-the job training, Internal NSA courses, and external training will be made available based on the need and experience of the selectee. Salary Range: $106,823 - $176,300 (Senior - Expert) NSAW location.