SAS Programmer/Data Manager- Remote

4 weeks ago


Reston, United States ICF Full time

ICF's Research Science, Survey Solutions, and Data Modernization Portfolio is seeking a SAS Programmer/Data Manager

The successful candidate will work as part of a team with data managers, analysts, statisticians, and project managers. They will be responsible for developing and implementing data management processes, writing data cleaning specifications and code, supporting preparation of analytical plans, sampling, and weighting, and creating codebooks and other data documentation. This position can be fully REMOTE. Key Responsibilities:

Design, implement, and maintain efficient data cleaning and management programs and procedures to meet client needs and prepare data deliverables. Develop and maintain documentation of data management and quality control procedures. Support senior statistical staff in coding and producing descriptive and basic weighted statistics. Contribute to technical report development and writing. Support innovation in solutioning complex data management challenges. Work in a cross-team/matrixed environment. Basic Qualifications:

Bachelor's degree in Survey Research/Methods, Statistics, Biostatistics, Epidemiology, Public Health, Mathematics, or other relevant statistical or social science field. At least 3 years of applied and demonstrable SAS experience using SAS for survey data management or analysis: Base SAS Procedures such as FREQ, TRANSPOSE, APPEND, FORMAT, DATASETS, REPORT, MEANS, UNIVARIATE, TABULATE. Advanced SAS techniques such as arrays, macros, PROC SQL. Knowledge of Microsoft Office products including Excel, Word, and PowerPoint. Preferred Qualifications:

Master's degree in Survey Research/Methods, Statistics, Biostatistics, Epidemiology, Public Health, Mathematics, Data Sciences, or other relevant statistical or social science field. Base or Advanced SAS certifications. Experience conducting statistical analyses using univariate, bivariate (e.g., Chi-squared, t-test, etc.) and multivariate analysis (e.g., logistic regression) methods, and calculating survey estimates accounting for sample design. Hands-on experience with other statistical programming or scripting languages (R, SPSS, Stata, Python, SQL). Experience supporting the design and application of sampling techniques (e.g., simple random samples, stratified samples, and multi-staged samples), calculation of survey weights, nonresponse analysis, and nonresponse adjustments. Strong problem-solving and critical thinking skills as it relates to data solutioning. Ability to communicate with internal and external clients at all levels to obtain or clarify project requirements. Professional Skills:

Excellent written and oral communications skills. Strong organizational skills. Detail-oriented. Ability to manage time effectively and work independently. Strong intellectual curiosity. Team-oriented.

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