Statistical Programmer

• Responsible for supporting clinical trial data analysis by developing and validating CDISC-compliant SDTM and ADaM datasets using SAS. Assist in generating statistical outputs (tables, listings, and figures) for Phase I-V studies in line with FDA submission standards. Apply foundational knowledge in probability, regression, statistical inference, and experimental design to ensure data quality and analysis accuracy. Collaborate with statisticians and cross-functional teams to interpret analysis plans and specifications.

Strong knowledge of SAS programming including DATA step, PROC SQL, and use of SAS procedures for data management and analysis. Strong knowledge of generate tables, listing, and figures and debug SAS code and optimize programs. Strong knowledge of statistical inference, including Maximum Likelihood Estimators, hypothesis testing, confidence intervals, and power analysis such as sample size calculation. Strong knowledge of experimental design methods, including ANOVA tables, randomized complete block design, Latin square design, balanced incomplete block design, factorial design, nested design, and split-plot design. Strong knowledge may be gained through educational coursework, training, or experience.

Minimum Education Required

Bachelor's degree in statistics or a closely related field., * Bachelor's degree in statistics or a closely related field.

• Strong knowledge of SAS programming including DATA step, PROC SQL, and use of SAS procedures for data management and analysis.

• Strong knowledge of generate tables, listing, and figures and debug SAS code and optimize programs.

• Strong knowledge of statistical inference, including Maximum Likelihood Estimators, hypothesis testing, confidence intervals, and power analysis such as sample size calculation.

• Strong knowledge of experimental design methods, including ANOVA tables, randomized complete block design, Latin square design, balanced incomplete block design, factorial design, nested design, and split-plot design.

• Strong knowledge may be gained through educational coursework, training, or experience.