Job Details

ID #3980162
Estado New York
Ciudad Newyorkcity
Full-time
Salario USD TBD TBD
Fuente Research Foundation CUNY
Showed 2020-05-21
Fecha 2020-05-22
Fecha tope 2020-07-21
Categoría Etcétera
Crear un currículum vítae

Senior Research Associate

New York, Newyorkcity 00000 Newyorkcity USA

Vacancy caducado!

Job Title: Senior Research AssociatePVN ID: VA-2005-003598Category: ResearchLocation: OFFICE OF SR. UNIV DEAN FOR ACADEMIC AFFAIRSKey FeaturesDepartmentOffice of Research, Evaluation, & PrograStatusFull TimeSalaryDepends on QualificationsClosing DateJul 03, 2020 (Or Until Filled)Actions

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Job DescriptionGeneral DescriptionIn Office of Research, Evaluation, & Program Support (REPS) of CUNY to work on evaluation and research projects pertaining to K16/college readiness initiatives and programs; Conduct formative and summative evaluations by applying quantitative and qualitative methods to assess programs and initiatives within SUD, drawing upon primary and secondary data (e.g. CUNY, NYCDOE, USDOL administrative data); Manage all phases of program evaluation projects; Engage in collaborative relationships with program partners to facilitate evaluation projects (including collecting, and processing student- and school-level data); Develop publication-ready data visualizations using multiple data sources; Migrate existing reports/develop new analytical dashboards using business intelligence tools to share ongoing insights with CUNY stakeholders; Manage program databases and external administrative data pre-processing for office-wide use; Summarize findings from statistical models for strategic decision-making; Manage project teams and supervise research staff; Present research and evaluation findings & recommendations to stakeholders; Prepare manuscripts for publication in academic journals.Other DutiesQualificationsMaster’s degree in Sociology.Minimum 1-year experience in managing research or evaluation projects, developing dashboards and reports, merging/manipulating/analyzing/interpreting large scale datasets including data cleaning; Advanced knowledge and strong skills in research and evaluation methods - qualitative and quantitative, including knowledge of statistical methods, machine learning techniques, i.e. descriptive statistics, inferential statistics, hypothesis testing, regression, multilevel modeling, clustering, classification trees, focus groups, interviews, survey analysis; Proficient in R, STATA, SPSS, SQL, Tableau, R Shiny.

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