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

The Senior Data Analyst will support several projects led by Dr. Noa Krawczyk, Assistant Professor and Associate Director of the NYU Langone Center for Opioid Epidemiology & Policy (COEP). The analyst will join an interdisciplinary team of epidemiologists, policy researchers, clinicians and data scientists studying how to improve access to, quality of, and outcomes of substance use disorder treatment across health systems and community settings. The Senior Data Analyst will serve as the primary quantitative analyst on several projects and work closely with investigators to manage complex datasets, implement analytic plans, and produce reproducible analyses that support publications, grant proposals, and policy-relevant research outputs. Analytic approaches used across projects include regression modeling, causal inference methods (e.g., difference-in-differences), machine learning (e.g. state sequence analysis) and simulation modeling. This role is ideal for an someone with prior experience working in academic environments, strong programming and analytic skills, ability to independently lead and execute analyses to achieve study aims, and who enjoys collaborating with researchers and policy partners to translate data into actionable insights.

Job Responsibilities:

• Compile, clean, merge, harmonize, and maintain databases from multiple administrative and research data sources.
• Conduct descriptive and inferential statistical analyses and interpret findings from diverse research datasets.
• Apply and adapt quantitative methods used across projects and learn/apply new methods as needed.
• Collect and compile data from novel sources, including public records and web-scraped data when relevant.
• Assist investigators in developing analytic plans and implementing appropriate statistical approaches.
• Prepare analytic outputs and summaries and collaborate with investigators on interpretation of findings.
• Develop tables, figures, and other materials for manuscripts, reports, and presentations.
• Participate in manuscript development, revision, and submission and assist with literature reviews as needed.
• Maintain regular communication with project team members and assist with grant submissions, data use agreements, and other project management tasks as needed.

Minimum Qualifications:
To qualify you must have a Bachelor's Degree and 3-5 years of experience required.

Preferred Qualifications:
A Masters or doctorate in epidemiology, data science, biostatistics or a related field (e.g., public health, health policy/services, health economics, sociology).
Demonstrated experience independently applying epidemiologic and econometric methods to public health research questions
Experience analyzing large healthcare datasets (e.g. claims, administrative records) and merging/synthesizing data across multiple sources
Ability to gather, organize, analyze, and report findings from analyses, including in the form of tables and multiple graphics
Strong programming and analysis skills using R, Stata, Python and/or SAS
Experience working in academic or public health research settings, with contribution to scientific publications.
Willingness and ability to learn new methodological techniques
Ability to work in a fast-paced environment both independently and collaboratively on interdisciplinary teams.
Ability to commute to mid-town NYC a minimum of 2 times/week
Preferred Qualifications:
Experience and interest in applying a range of quantitative methods (specifically regression analysis, difference in differences, state sequence analysis, computer simulation modeling, qualitative comparative analysis)
Ability to independently manage and lead segments of projects, analytic plans and team meetings as needed
Interest and enthusiasm for learning or applying new methods (both quantitative and qualitative) that best suit to or adapt to research project needs, including rapidly evolving large language models.
Interest in or prior experience working on issues of substance use treatment and overdose
Prior experience analyzing and merging large administrative, clinical, or claims datasets (e.g., Medicaid, EHR, treatment registry data).

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. At NYU Langone Health, we are committed to supporting our workforce and their loved ones with a comprehensive benefits and wellness package. Our offerings provide a robust support system for any stage of life, whether it's developing your career, starting a family, or saving for retirement. The support employees receive goes beyond a standard benefit offering, where employees have access to financial security benefits, a generous time-off program and employee resources groups for peer support. Additionally, all employees have access to our holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care. The benefits and wellness package is designed to allow you to focus on what truly matters. Join us and experience the extensive resources and services designed to enhance your overall quality of life for you and your family.

NYU Grossman School of Medicine is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. We require applications to be completed online.

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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 $70,481.60 - $105,000.00 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.

To view the Pay Transparency Notice, please click here