Biostatistician

Leidos•Houston, TX

1d•Onsite

About The Position

On the Human Health and Performance Contract, we are at the forefront of safeguarding astronaut health, optimizing human performance, and advancing technologies for human space exploration. We are seeking a Biostatistician to support these efforts at NASA Johnson Space Center (JSC) in Houston, TX. In this role, you will support advanced life sciences research initiatives, including human performance and spaceflight health studies. Responsibilities include designing robust statistical methodologies, analyzing complex datasets, and ensuring compliance with regulatory standards to advance scientific understanding and operational decision-making. Must be a U.S. Citizen or U.S. Permanent Resident due to the length of investigation required for non-U.S. persons.

Requirements

Master’s in Biostatistics, Statistics, or a related field, with at least 3 years of experience.
Progress towards a relevant PhD may be considered experience.
Strong foundation in experimental design and clinical research statistics
Proficiency in statistical software such as R, SAS, Stata, and/or Python (including libraries such as Pandas, SciPy, and Statsmodels)
Expertise in advanced statistical methods (e.g., Bayesian, multivariate, longitudinal analysis)
Experience in human performance, spaceflight health, or aerospace medicine research
Familiarity with regulatory compliance and ethical standards in human research
Experience with data visualization tools (e.g., ggplot2, matplotlib) and machine learning frameworks

Nice To Haves

Accuracy & Quality of Analysis: Percentage of statistical models validated and approved without major revisions
Timeliness: Average turnaround time for delivering statistical reports and analyses
Regulatory Compliance: Zero compliance violations in IRB, FDA, or GLP audits
Impact on Research Outcomes: Number of studies where statistical input significantly influenced design or conclusions
Collaboration Effectiveness: Positive feedback from interdisciplinary teams on clarity and usefulness of statistical insights
Innovation & Continuous Improvement: Implementation of advanced methods (e.g., Bayesian, machine learning) in a defined percentage of projects annually

Responsibilities

Develop statistical plans for experimental and observational studies
Perform power analyses and sample size calculations
Apply advanced statistical techniques, including mixed-effects models, survival analysis, and Bayesian inference
Clean, structure, and validate large, multidimensional datasets
Build predictive models and conduct longitudinal data analysis
Implement machine learning approaches for biomedical and physiological data
Ensure adherence to FDA, IRB, and GLP standards
Document statistical methodologies for audits and peer review
Collaborate with human health and performance researchers, clinicians, and engineers
Present findings through clear visualizations and technical reports