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Clinical Epidemiology and Data Science Co-op

Job in Danvers, Essex County, Massachusetts, 01923, USA
Listing for: Johnson & Johnson MedTech
Full Time position
Listed on 2026-09-22
Job specializations:
  • Healthcare
    Clinical Research, Medical Science, Data Scientist
  • Research/Development
    Clinical Research, Medical Science, Research Scientist, Data Scientist
Salary/Wage Range or Industry Benchmark: 33000 - 72000 USD Yearly USD 33000.00 72000.00 YEAR
Job Description & How to Apply Below

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, and solutions are personal.

Through our expertise in Innovative Medicine and Med Tech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.

Learn more at

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function

Career Programs

Job Sub Function

Non-LDP Intern/Co-Op

Job Category

Career Program

All Job Posting Locations

Danvers, Massachusetts, United States of America

Job Description

Johnson & Johnson is currently seeking a Clinical Epidemiology and Data Science Co-op to join our Advanced Clinical Research group located in Danvers
.

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and Med Tech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow and profoundly impact health for humanity.

Learn more at
.

The Advanced Clinical Research team uses real-world clinical and hemodynamic data to generate evidence, extend understanding of patient physiology and outcomes, and identify promising directions for future research. This co-op is designed for a student interested in the intersection of epidemiology, biostatistics, and data science, with an emphasis on clinical discovery. Working primarily with a clinical scientist and engage with cross-functional partners, the co-op will focus on a set of well-defined analytical questions across multiple studies.

  • Develop and execute reproducible statistical analyses of observational and longitudinal clinical data, including cohort and endpoint definitions, exploratory analyses, modeling, sensitivity analyses, and clear documentation of assumptions and limitations.
  • Use R or Python and, where appropriate, SQL to clean, structure, visualize, and analyze complex datasets containing clinical outcomes, patient characteristics, and hemodynamic measurements. Document analyses in a reproducible environment such as a Jupyter Notebook or Quarto.
  • Collaborate with scientists, clinicians, engineers, and other cross-functional partners to interpret findings, communicate results through written summaries and presentations, and recommend clinically meaningful questions or directions for future research.
Requirements

The Advanced Clinical Research team uses real-world clinical and hemodynamic data to generate evidence, extend understanding of patient physiology and outcomes, and identify promising directions for future research. This co-op is designed for a student interested in the intersection of epidemiology, biostatistics, and data science, with an emphasis on clinical discovery. Working primarily with a clinical scientist and engage with cross-functional partners, the co-op will focus on a set of well-defined analytical questions across multiple studies.

  • Develop and execute reproducible statistical analyses of observational and longitudinal clinical data, including cohort and endpoint definitions, exploratory analyses, modeling, sensitivity analyses, and…
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