APPLICATION INSTRUCTIONS:

• CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.

• CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.

• If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

This position is funded for 12 months; continuation past 12 months will be based on university need, performance, and/or availability of funding.

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POSITION SPECIFICS​

The Child Health Research Center in the College of Health and Human Development, University Park, PA, is seeking a Senior Professional Biostatistician. This position will play a vital role in supporting interdisciplinary research aimed at improving child health outcomes.  

   

What You'll Do:

Details include (but are not limited to): 

Study Design & Methodology 

• Consult and advise researchers on study design, statistical analysis strategies, reliability, data collection procedures, statistical power, sample size, and randomization schemes. 

• Oversee the design, development, and coordination of study forms, instruments, measurement protocols, and equipment. 

Statistical Analysis & Programming 

• Perform statistical analyses using SAS or other statistical software packages, including writing programs for treatment randomization, data summaries, and inferential analysis. 

• Apply and interpret complex statistical models (e.g., regression, mixed models, survival analysis, longitudinal data analysis). 

• Read and interpret findings, address gaps, and draw conclusions to inform research and policy. 

Data Management & Quality Assurance 

• Develop and oversee data management systems across multiple ongoing research projects. 

• Implement quality improvement practices and processes to ensure data integrity and reproducibility.