2027 Future Talent Program - Epidemiology and RWE Capabilities & Analytics - Intern

Merck • Boston, MA

3d • $39,908 - $111,111 • Hybrid

About The Position

The Future Talent Program features internships that last 10-12 weeks and will include one or more projects. These opportunities can provide you with great development and a chance to see if we are the right company for your long-term goals. The Biostatistics and Research Decision Sciences (BARDS) Epidemiology and RWE Capabilities & Analytics is seeking 2027 summer interns. The interns will have the opportunity to present their research work in internal or external professional forums or meetings. In addition, the interns will attend departmental and project team meetings to gain a broad perspective on the application of epidemiology and statistical method in the pharmaceutical industry. We are seeking intern candidates with strong academic performance, communication skills, spirit of teamwork, and the ability to work in a multi-functional environment.

Requirements

• Candidates must be a currently enrolled graduate student pursuing a PhD degree in epidemiology, biostatistics, public health, data science, biomedical informatics, or other closely related field; Or a currently enrolled graduate student pursuing a PharmD degree with relevant training in epidemiology
• Candidates will have completed at least 2 semesters of graduate work towards a PhD degree in epidemiology, biostatistics, public health, data Science, biomedical Informatics, or other closely related field by May 30, 2027; or towards a PharmD degree with relevant training in epidemiology by May 30, 2027.
• Candidates must be able to commit to full-time employment for 10 - 12 weeks beginning in May or June 2027.
• Candidates must be scheduled to return to school in Fall 2027, unless the internship is a requirement for their degree.
• Candidates must have effective oral and written communication skills.

Nice To Haves

• Candidates should have prior literature review (systematic/target) experience, have a good understanding of real-world data and real-world databases and have a good knowledge of SAS, SQL, R, or Python.
• Students with an interest in genetics/biomarkers, geospatial analysis, policy, or patient-reported outcomes/clinical outcomes assessments (PROs/COAs), data science, model development, artificial intelligence/machine learning are encouraged to apply.

Responsibilities

• Summarizing background information of a specific topic via targeted literature review
• Conducting data analysis in real-world health data sources to understand data quality, disease identification or treatment patterns, develop and validate prediction models
• Summarizing and interpreting study results
• Contributing to protocol development and manuscript writing
• Contributing to development and update of visualization tools (e.g., dashboard, geospatial visuals) of real-world data
• Contributing to development of materials to understand artificial intelligence and machine learning methods
• Communicating findings to an internal or external audience

What This Job Offers

• Job Type: Full-time
• Career Level: Intern