Biostatistician (Epidemiology) – Hybrid, Longitudinal Data

The Chronicle Of Higher Education, Inc.; Baltimore (MD); Hybrid; USD 55,800 - 97,600; Full time

Job summary

Johns Hopkins is seeking a Biostatistician to analyze large-scale longitudinal data from electronic health records, laboratory and pharmacy databases, and patient-reported outcomes surveys. You will contribute to study design, data management, quality control, and analyses for observational studies, and coauthor manuscripts.

Responsibilities include expanding SAS and R programs, data cleaning, generating analytic datasets and tables, and presenting results at scientific meetings.

Qualifications

• Master's degree in biostatistics, epidemiology, or related quantitative field.
• Additional education may substitute for required experience, tothe extent permitted by the JHU equivalency formula.

Responsibilities

• Use and expand SAS and R programs to clean and organize data.
• Identify problems with study data and collaborate with data managers to resolve issues.
• Read concept sheets and draft statistical analysis plans for research objectives.
• Generate analytic data sets, codebooks, and other documentation.
• Analyze individual-level data to answer scientific questions of interest.
• Prepare data tables and figures for publication and presentations.
• Contribute to technical writing and review drafts of concept sheets, reports, posters, and manuscripts.
• Document decision making and archive code for reproducibility.
• Attend meetings and provide status updates on data processing and projects.

Skills

Biostatistical Analysis

Data Management

Data Interpretation

Scientific Writing

Education

Master's Degree in biostatistics/epidemiology

JHU equivalency formula considered for experience

Tools

SAS

R

Job description

Johns Hopkins is seeking a Biostatistician to analyze large-scale longitudinal data from electronic health records, laboratory and pharmacy databases, and patient-reported outcomes surveys. You will contribute to study design, data management, quality control, and analyses for observational studies, and coauthor manuscripts.

Responsibilities include expanding SAS and R programs, data cleaning, generating analytic datasets and tables, and presenting results at scientific meetings.