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Join AIR as a Communications Assistant Intern with our Education Statistics team during our 2024 Virtual Summer Internship Program. The mission of our Education Statistics team is to provide
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American Institutes for Research | Southern Md Facility, Maryland | United States | about 1 month ago
Join AIR as a Communications Assistant with our Education Statistics team. The mission of our team of experts is to provide statistical evidence that is meaningful, timely, accurate, and
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using standard programming languages Support quantitative and/or qualitative analysis using standard statistical techniques and methods Support with modeling, simulation, and simple to moderately complex
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including fiscal data detailing school and district expenditures. Expertise in advanced social and behavioral science statistical methods including the use of regression models and rigorous program evaluation
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research proposals. Mentor research analysts + manage projects. Serve as client contact for analytical + statistical expertise. Little domestic and international travel may be involved. May undergo
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quantitative analyses Organizing and documenting analytical results and research procedures (e.g., data collection, instrument preparation, and statistical analyses) Preparing technical reports Designing and
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insights. Education, Knowledge, and Experience: Must be a student (for the duration of the internship) currently enrolled in a PhD program in pure or applied mathematics, statistics, data science, computer
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for data applications Experience with Python web frameworks – Django, flask – is a plus but not required Experience with statistical packages like R or SAS is a plus but not required Skills: Comfortable with
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languages Support quantitative and/or qualitative analysis using standard statistical techniques and methods Support with data analysis and data preparation Transform, clean, and visualize data from a variety
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quantitative data using appropriate statistical and/or psychometric methods (multiple linear regression, HLM, Structural Equation Modeling, IRT, etc.) Lead the design and planning of research studies using quasi