Statistical Programmer 4

4 weeks ago


Durham, United States ACL Digital Full time

schedule: M-F core hours being 10-3 EST with some flexibility - must be 8 hours a day/40 hours week

Working in a Team of: 4-7
Personality style: Looking for someone who is proactive and engaging. Not afraid to ask questions.
Candidate Introvert/Extrovert: Extroverted - will have client contact
How will performance be measured: Project reviews and progress through deliverables
MUST HAVE:
Experience with Statistical Programming in a clinical trial setting
SDTM/ADaM expertise
Knowledge of SAS
Experience writing specs/programming SDTM/ADaM datasets
Experience creating outputs using Proc report
High attention to detail

NICE TO HAVE:
Statistics degree
Experience with programming questionnaire data
Experience managing timelines and budgets
Experience being a lead of a study team or projects

EDUCATION:
BS in Computer Science, Mathematics, or Statistics

Summary: The main function of the Statistical Programmer is to use broad technical and data analysis skills, as well as business and industry knowledge, to identify client needs for quantitative analysis.
Job Responsibilities: Experience building regression-based models and using other modeling techniques. Hands-on SAS experience. SQL experience preferred. Skills: Perform data analysis, experimental design, and sample size determination in support of product R&D, process improvement/optimization, quality control, regulatory submissions, marketing research, and strategic decision-making. Apply current statistical methods when appropriate, and develop new methods when necessary. Determines relevant quantitative methods for solving client marketing issues. Assists in presenting ideas and findings to future and existing clients. Evaluates and improves internal tools and processes. Write
reports and make oral presentations as required. Knowledge/coursework in mathematical statistics, linear statistical models, regression, nonparametrics, Bayesian inference, stochastic processes and applied probability, multivariate analysis, and categorical data analysis required. Knowledge/coursework in Six Sigma continuous improvement,
statistical quality control, survey sampling, nonlinear regression and empirical modeling, modern regression methods, generalized linear models, optimization, and simulation preferred. Working knowledge of SAS or S-plus/R required. Knowledge of one or more general programming languanges, such as C++, Visual Basic, or Python preferred. High attention to detail. Strong problem-solving skills.



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