Biostatistician I Jobs (NOW HIRING)

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.

Job Function

The Biostatistician I will 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. Responsibilities include preparing and analyzing complex longitudinal and spatial datasets, under the direction of principal investigators, developing analytic strategies aligned with study aims, translating findings into actionable scientific outputs, and developing charts and graphs to display results; may assist in writing research papers for publication, presentations, or preparing statistical reports for management.

Specific responsibilities include:

• Leading geospatial analyses of tobacco retailer density, cannabis dispensary density, and neighborhood-level socioeconomic indicators.
• Cleaning, managing, and integrating large-scale longitudinal, survey, and geospatial datasets.
• Estimating the independent and joint effects of tobacco and cannabis retail environments on adolescent nicotine and cannabis vaping initiation and progression.
• Examining moderation by individual- and neighborhood-level socioeconomic disadvantage.
• Integrating and analyzing store observation data to identify characteristics of retail environments associated with adolescent vaping behaviors.
• Applying advanced statistical methods (e.g., multilevel modeling, longitudinal data analysis, spatial regression, causal inference approaches).
• Collaborating with the Principal Investigator and research team to interpret findings and refine analytic approaches.
• Contributing to manuscript preparation, conference presentations, and NIH progress reports.
• Supporting data visualization, reproducible workflows, and documentation of analytic procedures.
• Contributing to new grant proposals and ongoing projects within the lab.

Essential Skills and Characteristics

• 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

Basic Qualifications

The ideal candidate will have a Master's or PhD in biostatistics, statistics, epidemiology, data science, or a related quantitative field, along with demonstrated experience conducting advanced statistical and geospatial analyses. Candidates should be able to work both independently and collaboratively in a fast-paced research environment. Experience with NIH-funded research and peer-reviewed publications is preferred.

Minimum Education:

Master's degree or higher

Minimum Experience:

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

The annual typical salary for this position is $85,894.21. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.

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.

USC is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other characteristic protected by law or USC policy. USC observes affirmative action obligations consistent with state and federal law. USC will consider for employment all qualified applicants with criminal records in a manner consistent with applicable laws and regulations, including the Los Angeles County Fair Chance Ordinance for employers and the Fair Chance Initiative for Hiring Ordinance, and with due consideration for patient and student safety. Please refer to theBackground Screening Policy Appendix Dfor specific employment screen implications for the position for which you are applying.

We provide reasonable accommodations to applicants and employees with disabilities. Applicants with questions about access or requiring a reasonable accommodation for any part of the application or hiring process should contact USC Human Resources by phone at (213) 821-8100, or by email atuschr@usc.edu. Inquiries will be treated as confidential to the extent permitted by law.

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