Medical Data Scientist Intern - (Remote)

1 month ago

Merck & Co., Inc.

Full-time / Internship (Up to 12 weeks)$39,908 - $111,111 USD

Job Overview

Merck & Co., Inc. is offering a 12-week summer internship within its Healthcare Analytics Center of Excellence under the Value & Implementation Global Medical & Scientific Affairs division. Designed for university students passionate about applying data science to healthcare, this remote position focuses on using real-world data to evaluate oncology treatment landscapes, patient care journeys, and clinical profiles. Interns work alongside experienced quantitative researchers to process complex healthcare datasets, execute statistical models, and extract actionable insights that directly influence medical affairs strategy. Key activities involve literature synthesis, data manipulation, and applying analytical frameworks using languages like Python, R, SAS, and SQL. This position provides meaningful hands-on experience for students looking to translate analytical methodologies into impactful healthcare solutions within a major pharmaceutical research environment.

☑ Examine oncology literature and research resources to build domain knowledge for data-driven studies.
☑ Learn and execute analytical methods for evaluating real-world medical data, including claims datasets and electronic health records.
☑ Clean, structure, and process complex healthcare data in preparation for quantitative analysis.
☑ Perform statistical analyses and machine learning modeling utilizing tools such as Python, R, SAS, or SQL.
☑ Summarize analytical outcomes and present data findings clearly to team members and key Medical Affairs stakeholders.

☑ Current enrollment in an undergraduate degree program with at least two years of completed study.
☑ Foundational knowledge of statistics and quantitative data analysis principles.
☑ Working proficiency in at least one analytic programming language, such as Python, R, or SAS.
☑ Familiarity with Microsoft Office applications, including Excel and PowerPoint.
☑ Ability to communicate analytical findings clearly and effectively.
☑ Aptitude to work both independently and collaboratively within team environments.
☑ Possession of a valid driving license.
☑ Preferred background in quantitative fields like computational biology, computer science, engineering, psychology, neuroscience, or public health.
☑ Preferred exposure to graduate coursework, machine learning techniques, SQL databases, or web application frameworks like Shiny, Streamlit, or Dash.

☑ Fixed-term salary compensation ranging from $39,908 to $111,111 USD.
☑ Fully remote working arrangement.
☑ Structured professional development and project-based experience within the Research Labs Division.

This role may be suitable for undergraduate students in their junior or senior years who possess a strong quantitative foundation and an interest in healthcare data analytics. Candidates majoring in STEM disciplines like computational biology, computer science, or engineering, as well as social sciences with a quantitative emphasis, will find the work closely aligned with their academic background. It is well-suited for individuals comfortable manipulating real-world datasets in Python, R, SAS, or SQL and who enjoy translating statistical findings into practical insights. Because the position is fully remote with preference given to applicants in Pennsylvania or New Jersey, it offers flexibility for students aiming to gain industry experience at a global healthcare company.

Applicants may want to highlight academic coursework, technical projects, or research experience involving statistical analysis, machine learning, or real-world data processing. Emphasizing proficiency in analytical programming languages such as Python, R, SAS, or SQL on your resume will showcase technical readiness. Candidates with prior healthcare, life sciences, or clinical data exposure should detail those experiences prominently. Additionally, showcasing experience with data presentation tools like PowerPoint or interactive web frameworks such as Streamlit or Shiny can strengthen an application. Ensuring your CV clearly outlines completed undergraduate credits, current degree program, and relevant technical skill sets before submitting will support a thorough application evaluation.

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