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Position: STEM Data Analyst - Social Science/Humanities Research Associate
Institution: University of Texas at Austin
Department: Tides
Location: Austin, Texas, United States
Duties: Support CNS undergraduate education in designing and implementing appropriate research methods for collecting and analyzing data to measure the effectiveness of academic initiatives. Work with college leadership to design research questions surrounding the impact of the educational programs and student level data. Statistically analyze data and trends in enrollment and student academic performance using descriptive and inferential statistics. Conduct secondary research and produce reports of findings. Assist with the design and coordination of internal and grant-funded research studies. Manage and evaluate large databases on teaching and student performance data
Requirements: Master's degree with major coursework in quantitative data analysis techniques and research design in the natural or social sciences or education; two years of experience designing quantitative research projects in an educational setting; experience merging, managing, and analyzing large data sets using statistical programming packages to derive inferential statistics; excellent organizational and time management skills
   
Text: Social Science/Humanities Research Associate III - STEM Data Analyst Hiring department Tides Monthly salary $3,916 depending on qualifications Hours per week 40.00 Standard from 800AM to 500PM Posting number 17-08-09-01-4007 Job Status Open FLSA status Exempt Earliest Start Date 09/01/2017 Position Duration Terminates on 08/31/2020 Position open to all applicants Location Austin (main campus) Number of vacancies 1 General Notes Must be authorized to work in the United States on a full time basis for any employer. Position is for a three-year period, with possibility of extension based upon performance and funding. Required Application Materials A Resume is required in order to apply A Letter of Interest is required in order to apply. A List of 3 References is required in order to apply. Additional Information Purpose Support research efforts on student programs and education with the Texas Institute for Discovery Education in Science (TIDES) and the College of Natural Sciences (CNS). Essential Functions Support CNS undergraduate education in designing and implementing appropriate research methods for collecting and analyzing data to measure the effectiveness of academic initiatives. Work with college leadership to design research questions surrounding the impact of the educational programs and student level data. Statistically analyze data and trends in enrollment and student academic performance using descriptive and inferential statistics. Conduct secondary research and produce reports of findings. Assist with the design and coordination of internal and grant-funded research studies. Manage and evaluate large databases on teaching and student performance data. Perform detailed data-related activities (running database queries, data cleaning, data validation, data coding, etc.). Co-author research evaluation plans as part of grant proposals. Marginal/Incidental functions Other related functions as assigned. Required qualifications Master's degree with major coursework in quantitative data analysis techniques and research design in the natural or social sciences or education; two years of experience designing quantitative research projects in an educational setting; experience merging, managing, and analyzing large data sets using statistical programming packages to derive inferential statistics; excellent organizational and time management skills; proven written and oral communication skills; demonstrated ability to facilitate collaboration, engender support, and generate buy-in from a variety of stakeholders. Equivalent combination of relevant education and experience may be substituted as appropriate. Preferred Qualifications Doctoral degree in quantitative methods; experience writing grants for external funding; knowledge of natural sciences course work; familiarity with emerging issues in education research; familiarity with emerging issues in undergraduate science and math education; teaching or training technical information to non-technical audiences. Working conditions May work around standard office conditions Repetitive use of a keyboard at a workstation Use of manual dexterity
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