Statistician/Econometrician – R Programmer for Academic Statistical Research

We would like to search for a Statistician / Econometrician / R programmer with good statistical/econometrician knowledge with at least Difference and Difference regression and Time Series Regression Analysis experience, to develop R programs for us base of existing Difference and Difference, Regression Discontinuity Designs, and Generalized Synthetic Control R program. The position’s responsibilities and qualifications are described below. Work Period: From Immediately to 2-3 weeks Project Completion Compensation: Total project pay is determined by your availability, hourly rate, and the project’s workload/competency level. We would do flat rate only for the entire project Responsibilities 1. Programming/model implementation (main responsibility) -Base on existing Difference and Difference, Regression Discontinuity Designs, and Generalized Synthetic Control R codes, and inputting new panel data variables with different frequencies into the model to generate outputs -programming in R to code our models and create permutations, and various other programming, data, statistics related tasks. 2. Description of procedures: Provide detailed description of the methodology used models and implementation (at least in Difference in Difference model preferred) Qualifications 1. Master’s or PhD’s degree in Statistics/Econometric that used R significantly 2. Minimum 4 years of experience implementing programming using R (must), preferably statistical models 3. Statistical Analysis Experience Difference and Difference regression (must) Time Series Regression Analysis (must) Regression Discontinuity Designs Regression (preferred) Cox proportional hazard model used for survival analysis (preferred) 4. (Preferred) Have experience in Causal inference and using identification strategies 5. (Preferred) Have practical experience in implementing tests for detecting the presence of and methods for treating the endogeneity issues of reverse causality, simultaneity, omitted variable, and endogeneity in general 6. Preferred to have experience in applying statistical methodologies procedures to ensure robustness (such as to avoid multicollinearity, endogeneity, Heteroscedasticity, biases) (having experience in model diagnostic procedures) 7. Knowledgeable and years of practical experiences in basic and advanced statistical modeling, including many of the below statistical analysis methods, models, procedures • Regression analysis o Time series regression o Multivariate regression o Cox proportional hazard model (z-statistic) used for survival analysis (preferred) 8. Experience in academic research would be preferred 9. Very good English communications skills in oral and writing 10. Weekly availability to be at least 30 hours from now to end of March To apply, please answer the below questions 1. Do you have a Bachelor’s, Master’s, or Statistics degree in Statistics, Applied Mathematics, or closely related field? (please send a CV or resume with your application) 2. Number of years for R experience? 3. Approximately how often have you used R those years (such as 30 hours/w)? 4. Could you describe your R usage? Please include a more detailed description for the statistical programming usage, and a sample of a R script 5. What is your experience with Difference and Difference regression, Time Series Regression Analysis, and Regression Discontinuity Designs? 6. What is your weekly available hours that can dedicate to this work project up to 03/31? 7. Could you describe the extent of your statistical modeling experience? 8. Could you describe your experience in Causal inference and using identification strategies to setup appropriate experiment/tests that establish causal claims(possibly not needed)?