• Cleaned and updated 7,200 cases per month using SQL in SAS, ensuring data quality and timely delivery of data.• Automated exploratory descriptive analysis and routine reports generation analyzing over 72,000 cases in the past year with SAS Macro loops, significantly improving data processing efficiency.• Built interactive visualizations measuring time-series survey data using Tableau dashboard, generated geo-maps using R and ggplot2 to present how consumer index varies across states and counties, allowing data users to easily access and analyze data.• Implemented exploratory simulation research to test the matrix sampling methods, generated simulated data, utilized multiple imputation, and utilized various weighting methods, providing valuable insights into the potential benefits and limitations.• Improved coder consistency by measuring inter-coder reliability of six open ended questions and updated the coding rules.• Created Excel spreadsheets from SAS outputs to generate summarized descriptive statistics across multiple sheets and enabled comparisons among groups to identify statistical differences.

• Utilized logistic regression models and machine learning models to identify response patterns and predict respondent behaviors using R, providing insights for adopting the optimal survey modes to improve response rates.• Designed and tested surveys and analyzed survey data using R to understand attitudes of different candidates’ supporters toward social issues, providing strategies to achieve more electoral votes for an election candidate.• Programmed online surveys and sent surveys to potential respondents in the pool using Qualtrics and SurveyMonkey. • Developed analytic datasets from survey data and comprehensive documentation of data operations for six projects, including programming specifications, protocols, and codebooks.• Wrote technical reports on research findings to be submitted to clients and prepared presentation slides to stakeholders.

• Entered and re-coded data in SPSS and programmed validation rules to detect outliers and missing values.• Cleaned, validated and filtered 2,000+ cases, improving data quality and the accuracy of parameter estimators by identifying straight-liners, speeders and non-qualified respondents.• Conducted a thorough review of survey question development in the pre cog-lab stage and pre-pilot stage for longitudinal surveys, ensuring that the surveys were designed effectively and would provide accurate data, leading to higher quality results.• Developed focus-group interview protocols, recruited participants through social media, and implemented strategies to increase participation retention, resulting in higher participation rates.