Engineering Scientist – R&D Data Analyst

Applied Research Laboratories, The University of Texas at Austin

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Research and Development for data analysis applications and algorithms in cybersecurity and content understanding.

Essential Functions
Design, develop and evaluate algorithms and software in support of sponsored research projects. Contribute to research publications, evaluation reports, and software documentation. Prepare and deliver presentations of project updates and communicate effectively with team members and supervisors for timely implementation of project requirements.

Marginal/Incidental functions
Other related functions as assigned.

Required Qualifications
Bachelor’s degree and three years experience in engineering, computer and information science or other applied sciences. Strong math background. Demonstrated experience applying a wide variety of mathematical analysis techniques to multiple problem domains. US Citizen: Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information at the level appropriate to the project requirements of the position. Evidence of skills in the following areas: working with new technologies, being highly organized, planning and coordinating multiple tasks, effective time management, attention to detail, effective problem solving skills, using excellent judgment, working independently with sensitive and confidential information, maintaining a professional demeanor, working as a team member without daily supervision, effectively communicating with diverse groups of clients, working under pressure, accepting supervision and demonstrating regular/punctual attendance.

Preferred Qualifications
Master’s degree in computer science, mathematics or other applied sciences including advanced coursework or significant experience related to applying a variety of mathematical techniques (e.g., Monte Carlo methods, game theory, statistics, probability, graph theory) to analyze data. Experience with Python, R, and Matlab. Experience in both industry and academic research. Capability to communicate technical information to a variety of audiences as demonstrated by peer-reviewed publications, teaching experience, and/or tutoring programs. Cumulative GPA of 3.0.

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