Data Analyst - Department of Population Health
NYU School of Medicine is one of the nation's top-ranked medical schools. For 175 years, NYU School of Medicine has trained thousands of physicians and scientists who have helped to shape the course of medical history and enrich the lives of countless people. An integral part of NYU Langone Health, the School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care.
Position Summary:
We have an exciting opportunity to join our team as a Data Analyst.
We are seeking a qualified Data Analyst to provide support for data management and analyses for projects in the Division of Healthcare Delivery Science. The Data Analyst will mainly work with clinical, administrative and operational data, and be responsible for planning, designing, and implementing statistical analyses. A successful applicant will be able to work autonomously and comfortably in an academic medical center environment.
The Data Analyst will report to Dr. Saul Blecker in the Division of Healthcare Delivery Science and work closely with faculty in the Division of Biostatistics, both in the Department of Population Health. Projects will include a new federally funded initiative to develop and evaluate a system-level intervention to address medication adherence. The analyst will also collaborate in support of hospital clinical faculty in development and analyses of new research projects.
Job Responsibilities:
- Maintain and clean data from electronic health record (EHR) databases and other sources in support of research protocols and projects.
- Under supervision of research faculty and with the guidance of the teams lead biostatistician, conduct statistical analyses and present them to the team and collaborators.
- Support the development of publications and conference presentations, including drafting academic and nonacademic publications and creating tables and other data visualizations for presentations.
- Provide technical assistance to analysts and researchers in accessing and analyzing datasets, as needed.
- Perform reviews to ensure accuracy and completeness of data.
- Play an active role in providing clinical data for operational improvements.
- Interface with varied research collaborators, both within the School of Medicine and the Medical Center.
Minimum Qualifications:
- To qualify you must have a Masters degree in pertinent field (statistics; biostatistics; epidemiology; data science; healthcare economics) OR Bachelors degree with relevant work experience.
- At least 2 years of work experience and/or research experience in a relevant setting.
- Strong quantitative skills and advanced programming skills in R and/or SAS.
- Ability to select and apply appropriate statistical methods for collecting, summarizing, and analyzing EHR and other data.
- Excellent organization, time management, and communication skills.
- Knowledge of principles and methods of biostatistics; principles, theories, and procedures of epidemiology, including study design, statistical analysis, and causal inference.
- Ability to work both independently and as part of a collaborative research team.
- Experience with database queries and SQL is a plus.
Qualified candidates must be able to effectively communicate with all levels of the organization.
NYU Grossman School of Medicine provides its staff with far more than just a place to work. Rather, we are an institution you can be proud of, an institution where you'll feel good about devoting your time and your talents.
NYU Grossman School of Medicine is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sex, sexual orientation, transgender status, gender dysphoria, national origin, age, religion, disability, military and veteran status, marital or parental status, citizenship status, genetic information or any other factor which cannot lawfully be used as a basis for an employment decision. We require applications to be completed online.
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