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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 tomed.nyu.edu, and interact with us onLinkedIn,Glassdoor,Indeed,Facebook,TwitterandInstagram.

Position Summary:
We have an exciting opportunity to join our team as a Senior Research Scientist.

The New York University Grossman School of Medicine's Department of Population Health (DPH) is a dynamic environment of excellence, innovation and growth with faculty across a wide range of disciplines including behavioral and social sciences, epidemiology, health services research, evaluation, biostatistics, and medical ethics with a particular focus on health equity.

We are seeking a Senior Research Scientist with experience in substance use disorder and mental health research to work on multiple NIH-funded studies to improve quality of treatment for addictions. The Health Evaluation and Analytics Lab (HEAL) conducts healthcare research in partnership with government agencies to inform policies and improve the wellbeing of vulnerable populations. We use sophisticated analyses of large administrative data, qualitative data collection, and randomized trials of interventions targeting organizations to improve the effectiveness of clinical practices while addressing issues of race/ethnicity, gender, social determinants, and their intersections. We seek someone with robust analytical skills who can lead a team conducting studies with large data.

Exercise a high degree of creativity, foresight, and mature judgment in planning, organizing, and guiding scientific research projects and activities of outstanding novelty and/or importance.

Supervise a team of data analysts conducting advanced analyses with large administrative data.

Support all research activities, including qualitative studies and surveys.

Coordinate with partners-community-based organizations, healthcare providers, government representatives-on development and conduct of research.

Support development of study proposals for submission to funders.

Make significant contributions to scientific papers and serve as a resource/ author/ co-author for reports and presentations.

Initiate, interpret, organize, execute, and coordinate research assignments critical to HEAL's mission.

Develop and maintain a system for management of a multi-grant portfolio to ensure successful integration between projects.

Formulate and conduct research on problems of considerable scope and complexity.

Explore subject area and define scope and selection of problems for investigation through conceptually related studies or series of projects of lesser scope.

* Make decisions and recommendations that have a major impact on extensive scientific research activities.

Minimum Qualifications:
To qualify you must have a PhD and 3 years of experience or equivalent combination of education and experience.

Preferred Qualifications:

- PhD in health services research, public health, health policy, epidemiology, economics, psychology, or a related field;

- Minimum of 3 years experience in mental health, substance use disorder, or similar research, data management and statistical analyses;

- Minimum of 2-3 years of experience supervising others;

- Minimum of 2-3 years of experience with mixed methods studies;

- Outstanding verbal and written communication skills;

- Strong time-management and prioritization skills;

- Ability to work well under pressure and in a team;

- Experience working with key secondary data sources;

- Skilled in large-scale data manipulation;

- Highly proficient using SAS, STATA, R, Python and SQL;

- Experience developing data protection protocols and statistical analysis plans.

Only applications with a cover letter will be considered. To apply, email both a cover letter and resume to heal@nyulangone.org.

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.
If you wish to view NYU Grossman School of Medicine's EEO policies, please click here. Please click here to view the Federal "EEO is the law" poster or visit https://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm for more information.

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 $120,000.00-$140,000.00 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.

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