Biostatistician, Research Institute

CHOC Children's

Orange, California

Date Posted July 13, 2022
Industry Private Sector BioStat Jobs
Specialty Not Specified
Job Status Not Specified
Salary Not Specified

Description:

Work Location

Orange, California


Work Shift

Day – 08hrs (United States of America)

Why CHOC?

At CHOC Children’s, we strive to be the leading destination of children’s health by providing exceptional and innovative care. We are responsible for the overall health of our community’s pediatric population in our hospitals, clinics, and practices. And because of our breadth of care, your career at CHOC Children’s can be as diverse and fulfilling as you determine. CHOC Children’s compensation structure, benefits offerings, and career development programs are geared to helping you achieve your professional and personal goals. Apply now to see where your career at CHOC Children’s can take you.

Job Summary

CHOC is hiring a biostatistician with an epidemiology emphasis for the Biostatistics Core in the CHOC Research Institute. The ideal candidate will have experience in extraction, management and analysis of data from large health-care related administrative data bases (e.g., SEER, PHIS, NTDB, NIS, WISQARS), with strong analytic/statistical skills and experience providing support to investigators in study design, data extraction and analysis. Proficiency with R, SAS, SPSS, STATA, SQL, Python are highly desired as well as previous experience in an applied health research setting.

Under the direction of the Executive Director of the Research Institute at CHOC Children’s, the incumbent will provide support for biostatistical collaborative research, methodology research, and education. This includes biostatistical consultation to researchers, support on study design, data analysis, support for novel biostatistical methodology research, and data management and coordination. Responsibilities include mathematical modeling development, statistical programming and consultation support for investigators/scientists; running simulations for new and existing mathematical approaches to data analysis (including, but not limited to, survival analysis, generalized linear mixed models, and machine learning methods) arising from laboratory studies, clinical trials, and population-based studies; participating in consultations and discussions with researchers; assisting with the preparation of research papers, abstracts, and presentations; keeping current with related research literature; and contributing to grant proposal preparation for future funding. The incumbent is responsible working proactively and independently to managing multiple collaborative research projects and associated deadlines. Given the fluid nature of research projects in the Research Institute, the incumbent must have a strong interest in ongoing learning and education in an evolving scientific environment. The incumbent must demonstrate professional, analytical, and investigative skills to elicit information needed to clarify inquiries and requests or methods and procedures.

Experience:

  • Four or more years professional experience as an independent biostatistician (or similar position) working in a biomedical research setting.

  • Experience with collaboration/consultation - given the nature of their position, the biostatistician will work closely with biomedical and nursing research teams where regular consultations with researchers are expected. Strong record of co-authorship on collaborative biomedical and nursing research publications.

  • Experience with managing large datasets and large databases, including those designed for large longitudinal studies.

Education:

  • Master’s degree in biostatistics, statistics, or related quantitative fields combined with relevant coursework or experience

  • Prefers Doctoral degree in biostatistics, statistics, or related quantitative fields combined with relevant coursework or experience

Specialized Skills:

  • Proficient in Microsoft Office (Excel, Word, PowerPoint, etc.)

  • Broad and extensive knowledge of theoretical and applied statistics; this should include regression, logistic regression, linear, and generalized linear models; linear and generalized linear mixed models; survival analysis; longitudinal data; clinical trials methods; machine learning; epidemiologic methods; measurement error; prediction; propensity scores; and missing data imputation

  • Strong foundational training in mathematical statistics and probability

  • Highly proficient in SAS/SPSS and proficient in R

  • Experience in simulation programming in R

  • Basic knowledge of Stata

  • Basic understanding of relational databases

  • Exceptional organizational skills

  • Demonstrated ability to communicate (orally and in writing with English fluency) effectively and professionally with a variety of research personnel and colleagues with varying technical backgrounds

Licensure:

  • None required