HEOR Intern, Real-World Evidence

Essential duties include but are not limited to:

Help streamline internal processes – work directly with the Precision leadership to improve processes and efficiency; investigate optimal research techniques and implementation strategies; update existing tools and documentation to increase adherence to best practices; support development and refinement of interactive tools that use existing real-world evidence analyses.

Support ongoing research projects – assist with literature reviews on diverse healthcare topics; help with real-world evidence studies including protocol development, data programming, and results; develop interactive summaries of real-world evidence analyses; help interpret and communicate quantitative and qualitative findings to internal and external audiences; contribute to reports, results tables, presentations or peer-reviewed manuscripts; participate in client-facing activities; provide administrative project support.

Qualifications:

Required:

• Enrolled in a public health (epidemiology, biostatistics, bioinformatics), economics, data science, life sciences, or healthcare related undergraduate, or preferably, graduate program at an academic institution at the time of recruitment.

Other required:

• Proven interest in public health, life sciences, or pharmaceutical research and analytics
• Research experience in epidemiology, public health, health services research, health policy, economics or related fields
• Foundational knowledge of epidemiologic concepts such as observational study designs, measures of association, and common sources sources of bias and confounding
• Familiarity / competency with statistical programming tool such as R, SQL, SAS or similar platform
• Ability to work effectively both individually and as part of a team
• Detail oriented with exceptional interpersonal and time management skills
• Keen interest in learning and sharing knowledge
• Strong academic record
• Proficiency with Microsoft Office

Preferred:

• Enrolled in life sciences related advanced degree program
• Strong understanding of the scientific method; formal training in quantitative methodologies
• Familiarity with interactive data visualization tools such as R Shiny, Power BI, Tableau, or equivalent platforms
• Familiarity with working in virtual AWS environment, Git, and Github

Essential duties include but are not limited to:

Help streamline internal processes – work directly with the Precision leadership to improve processes and efficiency; investigate optimal research techniques and implementation strategies; update existing tools and documentation to increase adherence to best practices; support development and refinement of interactive tools that use existing real-world evidence analyses.

Support ongoing research projects – assist with literature reviews on diverse healthcare topics; help with real-world evidence studies including protocol development, data programming, and results; develop interactive summaries of real-world evidence analyses; help interpret and communicate quantitative and qualitative findings to internal and external audiences; contribute to reports, results tables, presentations or peer-reviewed manuscripts; participate in client-facing activities; provide administrative project support.

Qualifications:

Required:

• Enrolled in a public health (epidemiology, biostatistics, bioinformatics), economics, data science, life sciences, or healthcare related undergraduate, or preferably, graduate program at an academic institution at the time of recruitment.

Other required:

• Proven interest in public health, life sciences, or pharmaceutical research and analytics
• Research experience in epidemiology, public health, health services research, health policy, economics or related fields
• Foundational knowledge of epidemiologic concepts such as observational study designs, measures of association, and common sources sources of bias and confounding
• Familiarity / competency with statistical programming tool such as R, SQL, SAS or similar platform
• Ability to work effectively both individually and as part of a team
• Detail oriented with exceptional interpersonal and time management skills
• Keen interest in learning and sharing knowledge
• Strong academic record
• Proficiency with Microsoft Office

Preferred:

• Enrolled in life sciences related advanced degree program
• Strong understanding of the scientific method; formal training in quantitative methodologies
• Familiarity with interactive data visualization tools such as R Shiny, Power BI, Tableau, or equivalent platforms
• Familiarity with working in virtual AWS environment, Git, and Github