The fellow will work with a highly collaborative and multidisciplinary team of experts in epidemiology, biostatistics, and bioinformatics to develop a framework comprised of standardized analytic approaches to efficiently generate robust and reproducible real-world evidence across different tumor types, patient populations, and molecular biomarkers The fellow will conduct literature reviews, develop standardized analysis plans with input from key stakeholders, build and implement reproducible workflows, conduct analyses of different clinico-genomics databases, and lead training sessions to enable adoption of the framework across the department

• Lead the design, testing, and implementation of a comprehensive data analytics framework to guide the process of managing, analyzing, reporting, and interpreting real-world biomarker data
• Take part in epidemiologic research projects using real-world clinico-genomics data
• Solicit input from key internal stakeholders through written and oral communication
• Communicate research findings to cross-functional teams and internal stakeholders through written reports and oral presentations
• Disseminate research findings externally via scientific conference presentations and publications in peer-reviewed scientific journals
• Demonstrate leadership through process ownership and the training of colleagues to implement the developed framework
• Maintain and enhance professional knowledge and skills working in an industry setting

This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely

• Broad knowledge and experience in epidemiologic research and observational study design
• Strong quantitative skills with experience conducting statistical analyses in a clinical research setting
• Proficiency in statistical programming (SAS and/or R)
• Proven ability to complete research projects resulting in peer-reviewed scientific publications and conference presentations
• Strong organizational, problem solving, and troubleshooting skills
• Excellent written and verbal communication skills

Ability to plan and execute independent research, manage multiple projects, and collaborate effectively across multidisciplinary teams

• Candidate must hold a PhD, obtained within the last three years, or Ph.D. completed within 6 months of hire (e.g., PhD, DrPH, PharmD/MPH, MD/MPH, etc.) in epidemiology or public health, with a focus on cancer epidemiology and modeling
• Hands-on research experience using real-world data or other large-scale datasets (e.g., clinico-genomic databases, EHR, claims, registries)

Accountability, Accountability, Adaptability, Analytical Chemistry, Bioinformatics, Biostatistics, Cell Culture Techniques, Clinical Research, Computational Biology, Data Analysis, Epidemiology, Immunoassays, In Vivo Mouse Models, Management Process, Mathematical Biology, Molecular Biology, Multidisciplinary Collaboration, Multi-Management, Observational Studies, Oncology, Parasitology, Programming Languages, Project Reviews, Public Health, Scientific Research {+ 4 more}