Cancer Epidemiology: Applied Research Scientist II

Speros; Tampa (FL); Hybrid; USD 92,000 - 147,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

Paid time off

Parental leave

Job summary

Moffitt Cancer Center in Tampa, FL is seeking an APPLIED RESEARCH SCIENTIST II to lead informatics, data management, and analyses across cancer epidemiology projects. The role offers collaboration with Coghill Lab and a multidisciplinary team, with opportunities to co-author peer-reviewed work and present findings.

The ideal candidate has a PhD in a relevant field and strong R skills, REDCap experience, and a track record of managing complex clinical or molecular datasets, with independent

Qualifications

• Has strong applied research experience in epidemiology, biostatistics or data science.
• Experience with infections and cancer research or global work desirable.
• Advanced proficiency in R; experience managing complex clinical or molecular datasets.
• Experience leading statistical analyses and manuscript development.

Responsibilities

• Lead research informatics and database-management activities, integrating REDCap outputs with reproducible R workflows.
• Independently analyze clinical, epidemiologic, and molecular datasets; translate findings into figures, tables, presentations, and manuscripts.
• Provide scientific and operational oversight for multiple R01-funded projects; track milestones and progress; coordinate team members.

Skills

Applied research in epidemiology/biost

R proficiency

REDCap experience

Data science

Statistical analyses

Manuscript development

Education

PhD in epidemiology/biostatistics/data science/public health

Tools

REDCap

Job description

Moffitt Cancer Center in Tampa, FL is seeking an APPLIED RESEARCH SCIENTIST II to lead informatics, data management, and analyses across cancer epidemiology projects. The role offers collaboration with Coghill Lab and a multidisciplinary team, with opportunities to co-author peer-reviewed work and present findings.

The ideal candidate has a PhD in a relevant field and strong R skills, REDCap experience, and a track record of managing complex clinical or molecular datasets, with independent