Statistical Programmer Analyst
Statistical Programmer Analyst Hospitals & Healthcare Compensation depending on experience Monday-Friday, 8:00am- 5:00pmColumbus, Ohio (Hybrid)1-year contract Why You’ll Love This Job: Career development opportunities with an international company One-year contract, subject to renewal Equipment provided for job-related needs Collaboration with a team of highly skilled, cross-functional partners
What You’ll Do:
- Perform statistical analyses for nutrition research projects involving clinical trials and observational research
- Apply statistical methods, including analysis of variance and covariance, logistic regression, and causal analysis
- Use SAS programming to analyze research data and support statistical projects
- Manage, process, and analyze large datasets, including data wrangling and data mining
- Develop data visualizations, applications, and dashboards to communicate research findings
- Present statistical results to non-statistical audiences, including nutrition scientists, medical professionals, and clinical research staff
- Prepare detailed written reports documenting research methods, analyses, and findings
- Support data architecture, ETL/ELT pipelines, and data management workflows as needed
What We’re Looking For:
- Master's degree in Statistics, Biostatistics, or a related applied mathematical field.1-3 years of relevant experience
- Strong SAS programming skills, including experience with SAS macros, data steps, and PROC SQLExperience with statistical methods and data analysis applicable to clinical trials and observational research
- Proficiency in R or Python, including relevant data analysis and visualization libraries
- Experience with large datasets, data wrangling, and data management
- Familiarity with version control tools such as GitHub and database technologies such as Microsoft SQL Server
- Experience with data architecture, ETL/ELT pipelines, cloud environments, or high-performance computing is a plus
- Experience creating visualizations and dashboards using tools such as Tableau, Power BI, or programming-based visualization tools
- Strong written and verbal communication skills, including the ability to explain complex statistical findings to nontechnical audiences
- Familiarity with CDISC SDTM data structures is a plus
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