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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 Fruit Street
EEO Statement:
1200 The General Hospital Corporation is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law. We will ensure that all individuals with a disability are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. To ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Veteran's Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact Human Resources at
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