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Postdoctoral Research Scientist
Job in
Boston, Suffolk County, Massachusetts, 02298, USA
Listed on 2026-01-05
Listing for:
Mass General Brigham Incorporated.
Full Time
position Listed on 2026-01-05
Job specializations:
-
Healthcare
Data Scientist, Clinical Research
Job Description & How to Apply Below
Hybrid locations:
Boston-MAposted on:
Posted Todayjob requisition :
RQ4047056
Site:
The General Hospital Corporation Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
** Job Summary
** The Massachusetts General Hospital Department of Emergency Medicine is seeking a highly quantitative, motivated, research-oriented postdoctoral scientist with strong data science and statistical modeling expertise. The ideal candidate will have advanced coding skills and a strong interest in translating quantitative methods to important problems in healthcare delivery and population health. This individual will contribute to quantitative modeling to address issues of access in emergency care delivery, with a focus on stroke care access and the prehospital setting.
This individual will work under the general supervision of the Principal Investigator (PI) Dr. Zachrison and work collaboratively with Co-Investigators in the Columbia Healthcare Innovations Research and Evaluation Unit. This individual will be responsible for all aspects of data management and statistical analytic work for assigned projects. He/she will be a highly integrated team member interfacing with Investigators, Fellows, and other research staff on a regular basis.
** Qualifications
* **
* Principle Duties and Responsibilities:
** Specific responsibilities include:
Creating and maintaining a mathematical decision model. Using existing registry data to derive parameter estimates for incorporation into decision model. Working with Investigators on the development of the decision model and its use in related research questions. Drafting of Methods and Results sections for related manuscripts (with inclusion as co-author). Assist with grant applications (e.g., approach section) related to the decision model.
Maintain IRB files and communication with IRB for the study. Responsible for overseeing all data-related amendments to the IRB. Collaborates with Principal Investigator (PI) and Co-Investigators in performance of above duties.
*
* Skills Required:
** Must have experience with:
Data science or health services research and electronic data management systems. MS Office products. A specific statistical package (e.g., Python, R or equivalent)
Must have:
Doctoral degree (PhD) in quantitative field (data science, statistics, bioinformatics, applied math, or related discipline) Proficiency in programming and data science tools (Python, R, or equivalent) Strong statistical and machine learning background, with ability to develop and evaluate prediction models Excellent critical thinking and written and verbal communication skills. Excellent written and verbal communication skills. The ability to work well with a diverse group of individuals.
Preferred:
Prior experience with scientific publication (e.g., drafting manuscripts, conducting analyses, describing methods and results, etc.).
*
* Education:
** Field of Study/Additional Specialized Training:
Doctoral degree in statistics, data science, mathematics, or a healthcare-related discipline. Must have a strong background in statistics programs (such as Python, R, STATA) and database management (such as MS Access and Excel).
*
* Experience:
** Preferred:
Minimum of one year of data analysis experience is strongly preferred.
*
* Working Conditions:
** Normal indoor office environment.
** Additional Job Details (if applicable)
**** Remote Type
** Hybrid
* * Work Location
** 55…
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