Statistician I

University of Southern California•Los Angeles, CA

About The Position

The Center for Translational Exposomics Research on Environmental Health at the Department of Population and Public Health Sciences is in search of a dependable, flexible, and detail-oriented individual to join a dynamic research team at the University of Southern California to participate on multiple projects aimed at investigating the exposome, multi-omics, and health outcomes across the lifespan. Employment involves: (1) evaluating and implementing procedures for data management and quality control; (2) developing input methodology and data file structure; (3) performing data analysis using statistical methods, including analysis of complex biological datasets such as multi-omics and organoid-derived data, and reviewing results for anomalies and making corrections if necessary; (4) assisting in interpretation of results and preparing tables or graphs for inclusion in reports and research papers; and (5) assisting Principal Investigators in writing scholarly empirical papers for publication and presentation. The ideal candidate will have superb problem-solving skills and prior experience in a research environment and on working with chemical exposures including PFAS and multi-center study designs.

Requirements

Master's degree in Biostatistics, Statistics, or related field
Minimum of 1 years of relevant experience in biostatistics, statistics, computational biology, computer science or related disciplines
Strong statistical analysis skills; fluency in R is required
Experience analyzing large biological datasets (e.g. metabolomics, organoid, microRNA, etc.)
Experience with large and complex datasets
Excellent written and oral communication skills
Ability to work independently and as part of a team
Statistics, econometrics and/or biostatistics experience.
Experience with relevant data analysis programs (e.g., R, Python, SAS, SPSS).
Proven analytical and problem-solving skills.

Nice To Haves

PhD or equivalent doctoral degree
Experience analyzing large biological datasets (e.g. metabolomics, microRNA, etc.)
Experience developing code in a team environment using git/GitHub
3 years of preferred experience

Responsibilities

Collaborate with researchers to design and develop statistical analysis plans for research projects
Conduct statistical analyses using statistical software including R
Interpret and communicate statistical results to stakeholders, including researchers, clinicians, and funding agencies
Develop and implement quality control procedures to ensure accuracy and reliability of data
Prepare and review statistical reports and presentations
Aid in the development of manuscripts and extramural grant proposals
Participate in study design and data management
Collaborate with other team members on interdisciplinary research projects
Stay up to date with current statistical methods and attend relevant training or conferences
May supervise and mentor junior biostatisticians, postdocs, and graduate students