Biostatistician- The Child Health Research Center

The Pennsylvania State University•University Park, FL

3d•Hybrid

About The Position

The Child Health Research Center seeks a collaborative Biostatistician to serve as a statistical advisor, collaborator, and mentor in a multidisciplinary research setting. The position partners with investigators, clinicians, research staff, postdoctoral scholars, and students, supporting projects from initial study design through data management, analysis, and publication. The role is based at Penn State’s University Park campus with a hybrid work arrangement; remote work may be considered for exceptionally qualified candidates with demonstrated methodological leadership, publications, and cross-functional collaboration experience. The Biostatistician advises on study design, statistical methods, data collection, power, sample size, and randomization; conducts advanced analyses; and develops data-management processes and research data-collection tools. The position also supports grant development, manuscripts, technical reports, presentations, and data visualizations, and mentors developing researchers. The successful candidate will work independently across multiple projects, promote reproducible research, and help strengthen statistical knowledge across the Center. The position is funded for one year. Continuation beyond that period depends on university need, performance, and/or funding availability. Penn State does not sponsor employment visas; applicants must be authorized to work in the United States.

Requirements

Bachelor’s degree.
At least 3 years of relevant experience for the Advanced Professional level, or an equivalent combination of education and experience; at least 6 years for the Senior Professional level, or an equivalent combination.
Ability to collaborate with multidisciplinary teams and stakeholders with varying levels of statistical expertise.
Strong consultation skills and ability to explain complex statistical concepts clearly and approachably.
Proficiency analyzing large, complex datasets using advanced statistical techniques.
Deep understanding of linear, logistic, mixed-effects, longitudinal, and multilevel regression models.
Proficiency with R, SAS, or comparable statistical tools.
Experience designing and implementing data-collection protocols and managing datasets for analysis and reporting.
Skill in creating data visualizations and communicating findings through reports, manuscripts, grant proposals, and presentations.
Experience mentoring students, trainees, or junior team members in statistical methods and research design.
Ability to work independently as the sole methodologist within a larger institutional ecosystem and manage project priorities and timelines.
Proficiency in independent data cleaning, database structural design, data architecture preparation, and merging disparate or messy data sources.
Track record of reproducible research workflows, including clean, well-commented, version-controlled code suitable for audit and peer review.
Understanding of health-data privacy, data-sharing agreements, IRB statistical requirements, and secure management of sensitive human-subjects data.
Applicants must be authorized to work in the United States.
Required clearances include a Pennsylvania State Police Criminal Background Check, PA Child Abuse History Clearance Form, and Federal (FBI) Fingerprint Criminal Background Check.
No certifications are required.

Nice To Haves

Experience as a statistical consultant in a collaborative research, healthcare, academic, or clinical environment.
Demonstrated success mentoring students, trainees, or junior colleagues.
Experience working with interdisciplinary teams and diverse stakeholder groups.
Evidence of strong communication skills through presentations, teaching, publications, or collaborative research contributions.
Familiarity with statistical challenges in child-health, developmental, or clinical datasets, such as skewed pediatric growth metrics, complex longitudinal data, missing-data patterns, or family and sibling clusters.

Responsibilities

Consult with researchers on study design, statistical analysis strategies, reliability, data collection procedures, statistical power, sample size, and randomization.
Oversee the design and coordination of study forms, instruments, measurement protocols, and equipment.
Analyze large and complex datasets using R, SAS, or other statistical software, including regression, mixed-effects, and longitudinal methods.
Interpret findings, identify gaps, and translate results into insights that inform research and policy.
Develop and oversee data-management processes to ensure data quality, integrity, and reproducibility.
Advise on and develop REDCap projects, databases, surveys, and other secure data-collection tools.
Provide pre-award methodological support, including operationalizing research hypotheses, defining endpoints, constructing randomization schemes, and preparing sample-size and power justifications.
Translate statistical modeling strategies into methodological frameworks for multidisciplinary child-health research teams.
Troubleshoot data-integrity issues, improve reproducible statistical workflows, and resolve data-pipeline bottlenecks.
Co-author grant proposals, peer-reviewed manuscripts, and technical reports, including drafting methodology sections.
Prepare statistical reports and communicate findings through written summaries, data visualizations, and presentations.
Mentor postdoctoral scholars, graduate and undergraduate students, and other junior team members in research questions, analysis plans, statistical methods, and interpretation.
Share statistical knowledge and best practices and contribute to a culture of learning, innovation, and teamwork.
Manage multiple projects and priorities independently, including project timelines and priorities.