Data Analyst

1 week ago


New York, United States NYU Langone Full time

**NYU Grossman School of Medicine** is one of the nation's top-ranked medical schools. For 175 years, NYU Grossman 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 Grossman School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care. At NYU Langone Health, equity, diversity, and inclusion are fundamental values. We strive to be a place where our exceptionally talented faculty, staff, and students of all identities can thrive. We embrace diversity, inclusion, and individual skills, ideas, and knowledge. _For more information, go to _med.nyu.edu_, and interact with us on _LinkedIn_, _Glassdoor_, _Indeed_,_ _Facebook_, _Twitter_ and _Instagram_._

**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 Health Evaluation and Analytics Lab (HEAL). HEAL is a unique research resource that contains New York Medicaid and other state administrative data to support studies of health and healthcare. HEAL is a joint venture between DPH and the NYU Wagner School of Public Service. The mission of HEAL is to conduct research and evaluations that assist in the administration of the New York Medicaid program and contribute to national scholarship on health and healthcare.

The Data Analyst will work closely with faculty in the Lab on grant-supported addiction health services research. Projects will include a new federally funded study examining the long-term effects of existing treatment for opioid use disorders (OUD) among young adults. The analyst will also work on other projects that aim to make improvements to the quality of the addiction treatment system.

**Responsibilities**:

- Conduct analyses examining health and healthcare services
- Work effectively with large, complex administrative datasets to solve challenging problems
- Write programs to clean complex data and create analytic datasets from raw data
- Under supervision of research faculty 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
- Perform reviews to ensure accuracy and completeness of data

**Minimum Qualifications**:
To qualify you must have a Masters degree in pertinent field (statistics; biostatistics; epidemiology; data science; healthcare economics)
At least 2 years of work experience and/or research experience in a relevant setting.
Strong quantitative skills and advanced programming skills in SAS, Stata or R
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.

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 Langone Health provides a salary range to comply with the New York state Law on Salary Transparency in Job Advertisements. The salary range for the role is $62,400.00 - $74,200.00 Annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.

To view the Pay Transparency Notice, please click here


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