Biostatistician I

University of Southern California•Los Angeles, CA

About The Position

The Institute of Addiction Science (IAS), the Tobacco Center of Regulatory Science (TCORS), and the Real-World Evaluation in Behavioral Epidemiology Laboratory (REBEL) are seeking a highly motivated, detail-oriented Biostatistician I to join our multidisciplinary research team. This full-time position will play a central role in leading statistical and geospatial analyses for an NIH K01-funded study examining how the tobacco and cannabis retail environment and neighborhood disadvantage influence adolescent nicotine and cannabis vaping initiation and progression. The Biostatistician I will work closely with the Principal Investigator while collaborating with faculty, postdoctoral fellows, graduate students, and research staff across multiple ongoing cohort studies focused on adolescent and young adult behavioral health. This role offers opportunities to contribute to high-impact research, peer-reviewed publications, and future grant development.

Requirements

Master’s or PhD in biostatistics, statistics, epidemiology, data science, or a related quantitative field.
Demonstrated experience conducting advanced statistical and geospatial analyses.
Demonstrated expertise in complex statistical and geospatial analysis and interpretation.
Strong programming skills in R, SAS, Stata, and/or ArcGIS.
Experience working with multi-level, longitudinal, and spatial datasets.
Exceptional attention to detail and data quality.
Strong written and verbal communication skills, including the ability to translate statistical findings for interdisciplinary audiences.
Strong organizational skills and ability to manage multiple analytic projects simultaneously.
Interest in behavioral health, addiction science, and health disparities research.
Minimum 2+ years of experience in statistical analysis within a research setting (doctoral training may count toward experience).
Minimum Field of Expertise: Advanced statistical modeling, geospatial analysis (e.g., GIS, spatial-temporal modeling), and management of complex research datasets.
Minimum Education: Master's degree, Combined experience/education as substitute for minimum education.
Minimum Experience: 1 year, Combined education/experience as substitute for minimum experience.
Minimum Field of Expertise: Experience in Biostatistics, Statistics or related field.
Experience with SAS, R or STATA.

Nice To Haves

Experience with NIH-funded research and peer-reviewed publications is preferred.

Responsibilities

Lead and support advanced statistical and geospatial analyses across multiple projects, with a primary focus on a K01 study investigating environmental and socioeconomic determinants of adolescent vaping behaviors.
Prepare and analyze complex longitudinal and spatial datasets, under the direction of principal investigators.
Develop analytic strategies aligned with study aims.
Translate findings into actionable scientific outputs.
Develop charts and graphs to display results.
Assist in writing research papers for publication, presentations, or preparing statistical reports for management.
Lead geospatial analyses of tobacco retailer density, cannabis dispensary density, and neighborhood-level socioeconomic indicators.
Clean, manage, and integrate large-scale longitudinal, survey, and geospatial datasets.
Estimate the independent and joint effects of tobacco and cannabis retail environments on adolescent nicotine and cannabis vaping initiation and progression.
Examine moderation by individual- and neighborhood-level socioeconomic disadvantage.
Integrate and analyze store observation data to identify characteristics of retail environments associated with adolescent vaping behaviors.
Apply advanced statistical methods (e.g., multilevel modeling, longitudinal data analysis, spatial regression, causal inference approaches).
Collaborate with the Principal Investigator and research team to interpret findings and refine analytic approaches.
Contribute to manuscript preparation, conference presentations, and NIH progress reports.
Support data visualization, reproducible workflows, and documentation of analytic procedures.
Contribute to new grant proposals and ongoing projects within the lab.