Space Operations Risk Assessment Specialist

Salary/Position Classification 20 hourly, Non-Exempt (Eligible for overtime) 20 hours per week 100% Remote Work Availability: Yes Hybrid Work Availability (requires some time on campus): Yes Purpose of Position The UND Computational Research Center is seeking a risk assessment specialist with expertise in statistical risk assessment, failure probability analysis, and Bayesian statistical methods capable of translating this expertise into spacecraft failure prediction and uncertainty quantification. This position will work with a larger research team to develop AI models for predicting spacecraft failure. Duties & Responsibilities Work under the direction of the UND CRC Advanced Cyberinfrastructure Manager, and other designated researchers, to execute the following responsibilities: Conduct a literature review on Bayesian network applications in spacecraft reliability, failure analysis, and risk assessment Collect and curate failure data from relevant sources (e.g., spacecraft anomaly databases, mission reports, component reliability handbooks) Identify key failure modes, subsystems, and causal relationships to be represented in the Bayesian network Develop the network structure, including defining nodes, states, and dependencies in consultation with domain experts Elicit and estimate conditional probability tables from data, expert judgment, or hybrid approaches Implement and validate Bayesian network models using appropriate software (e.g., GeNIe, Netica, pgmpy, bnlearn) Perform inference, sensitivity analysis, and scenario testing to evaluate failure probabilities and identify critical contributors Document modeling assumptions, data sources, and limitations clearly and reproducibly Present results through regular progress meetings, written reports, and visualizations Contribute to manuscripts, conference papers, or technical reports as appropriate Collaborate with team members and incorporate feedback into iterative model refinement Required Competencies Demonstrated understanding of statistical risk assessment and failure probability analysis. Strong problem-solving skills and attention to detail Excellent written and verbal communication skills Minimum Requirements Bachelors of Science degree in Actuarial Science, Mathematics, or a related field. Experience programming using R, Python, and/or MATLAB Experience developing Monte Carlo simulations Export Control Compliance: This position requires compliance with U.S. government export control laws and regulations. Applicants are required to be eligible for employment under U.S. export control laws and must meet the requirement of being a “U.S. Person” (U.S. citizen, lawful permanent resident, or protected individual as defined by 8 U.S.C.1324b (a)(3)). UND will not sponsor applicants for employment authorization for this position. Information collected in this regard will only be used to ensure compliance with U.S. export control laws and will be used in compliance with all laws prohibiting discrimination on the basis of national origin and other factors. Successful completion of a Criminal History Background Check In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the US and to complete the required employment eligibility verification form upon hire. This position does not support visa sponsorship for continued employment.

Preferred Qualifications

Masters of Science degree in Actuarial Science, Mathematics, or a related field. Experience with Bayesian statistical methods Experience modeling rare, catastrophic failure events Experience developing AI models for assessing risk and failure prediction. Experience assessing risk and failure prediction for systems in remote, extreme physically inaccessible locations, such as a deep-sea environment or low-earth orbit. Experience using the GitHub collaborative software development platform. To Apply Please include resume/CV, cover letter, and other applicable documents to support you meet the minimum requirements and competencies. Apply To This Job