The Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health seeks a biostatistician to work jointly with faculty on the development and application of causal inference methods in a variety of substantive areas. The biostatistician will contribute to applied analyses of various data sources, including trials, surveys, cohorts, claims, and EMRs. The successful applicant will contribute to general research on translating advanced causal methodology to the applied research community. The position will be managed jointly by faculty in Epidemiology and Mental Health.
Specific duties & responsibilities:
The primary responsibilities for the position will involve data analysis and simulation experiment
Assemble analytic datasets with data dictionaries, develop and implement statistical analysis plans, and summarize results.
Design, implement, and analyze simulation experiments to evaluate the performance of statistical methods.
Review of the biostatistical literature and will often involve contributing to manuscripts for publication. Excellent oral and written communication skills are needed to collaborate with investigators from a variety of disciplines and to present findings with the potential to coauthor scientific papers.
Support multiple research projects, and must be proactive, resourceful, self-directed, highly organized, and able to work independently and efficiently.
Master's degree in biostatistics, epidemiology, or related quantitative field. 1 year related experience.
Demonstrated ability on a significant graduate projects or additional doctoral education may substitute for experience to the extent permitted by the JHU equivalency formula.
A strong background in statistics and causal inference methodology (e.g., propensity scores, marginal structural models, g-computation, etc.), applied data analysis, and simulation are required, along with proficiency in the R statistical computing language.
Research experience is preferred.
At least one year of experience analyzing applied data and carrying out simulation experiments.
Manuscript preparation and presentation also desirable.
Special knowledge, skills, and abilities:
Expertise in the R statistical computing language (additional proficiency with SAS is preferred).
Experience working in statistical computing environments (e.g., high performance clusters) also preferred.
Experience with causal inference methodology required, and knowledge of other advanced methods (e.g., machine learning, missing data imputation, sensitivity analysis) welcomed.
Classified Title: Biostatistician Working Title: Biostatistician Role/Level/Range: ACRP/04/MD Starting Salary Range: $52,495 - $72,210; Commensurate with experience Employee group: Full Time Schedule: Monday-Friday 8:30 a.m. - 5:00 p.m. Exempt Status: Exempt Location: 05-MD:School of Public Health Department name: 10001101-Epidemiology Personnel area: School of Public Health
The successful candidate(s) for this position will be subject to a pre-employment background check.
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