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 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 inclusion and individual skills, ideas, and knowledge.
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POSITION SUMMARY:

We have an exciting opportunity to join our team as a Senior Data Analyst.
In this role, the successful candidate About Us:
Join the Health Evaluation and Analytics Lab (HEAL) at NYU Langone Health, a collaborative initiative between the Department of Population Health (DPH) and NYU Wagner School of Public Service. HEAL leverages New York Medicaid and other state administrative data to advance health and healthcare research. Our mission is to enhance the administration of the New York Medicaid program and contribute to national health and healthcare scholarship.
Position Overview:
We are seeking a highly skilled and independent Senior Data Analyst to support and lead analytic activities within our Health Equity Regional Organizations (HERO) project portfolio. This position offers the opportunity to contribute to rigorous, policy-relevant research at the intersection of health services, health-related social needs, social care networks, and population health. The Senior Data Analyst will work in close collaboration with faculty investigators to develop and implement analytic strategies, manage large administrative datasets, and generate insights that inform clinical practice and policy. The ideal candidate will demonstrate strong methodological expertise, a commitment to advancing health equity, and the ability to mentor junior analysts and contribute to scholarly dissemination.

MINIMUM QUALIFICATIONS:

To qualify you must have a Master’s degree in a relevant field such as public health, epidemiology, biostatistics, health economics, data science, or a related discipline.
At least 4 years of relevant experience conducting data analysis in a healthcare, public health, or policy research setting.
Demonstrated expertise in working with large administrative health datasets (e.g., Medicaid, Medicare, EHRs), including managing data from raw form to analysis-ready datasets.
Advanced proficiency in R for data cleaning, transformation, statistical analysis, and visualization; proficiency in Stata, SAS, or Python is a plus.
Demonstrated expertise in understanding of data warehousing concepts and data modeling principles; data cleaning and validation, and attention to detail and a commitment to data quality.
Proven ability to manage multiple analytic workstreams, meet deadlines, and work independently with limited supervision. Strong problem-solving skills, attention to detail, and ability to manage competing priorities across multiple projects.
Experience contributing to scholarly publications or technical reports; authorship on peer-reviewed publications is a plus.
Excellent written and verbal communication skills, including the ability to explain complex analytic concepts to non-technical collaborators.
Experience mentoring junior staff or leading training in analytic tools or methods.
Strong experience using SQL to extract and query data from large relational databases.
Familiarity with version control systems (e.g., Git) and best practices in reproducible research, including the creation and maintenance of shared project documentation.

PREFERRED QUALIFICATIONS:

Experience with New York State Medicaid data or other state-based administrative health data systems.
Prior involvement in multidisciplinary academic research teams and contribution to grant-funded research projects.
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 $67,771.14 - $100,700.00 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.

JOB RESPONSIBILITIES:

• Lead the development and execution of analytic plans for health services research projects, including defining study cohorts, constructing variables, and conducting statistical analyses.
• Manage, clean, and analyze large and complex administrative datasets (e.g., Medicaid claims, health-related social needs data), including linked data sources.
• Develop and implement efficient methods for data extraction from various systems, ensuring data integrity during transfer.
• Establish and maintain secure connections to data sources.
• Design and implement robust data pipelines (ETL/ELT processes) to ingest data from identified sources into a centralized environment (e.g., data lake, data warehouse).
• Perform comprehensive data quality assessments to identify anomalies, missing values, duplicates, and inconsistencies.
• Develop and apply data cleaning techniques (e.g., imputation, outlier detection and treatment, standardization, de-duplication) to ensure data accuracy and reliability.
• Maintain clear data models and relationships between tables.
• Implement data validation rules and checks to maintain data integrity.
• Document data cleaning methodologies and rationale.
• Develop and implement logic to create new features and variables from existing raw data, enhancing the analytical value of the dataset.
• Transform and aggregate data at various granularities as required for reporting.

ADDITIONAL POSITION SPECIFIC RESPONSIBILITIES:

Contribute to the preparation of manuscripts, conference presentations, grant proposals, and technical reports, including drafting methods and results sections and developing data visualizations.
Ensure reproducibility and transparency in analytic workflows through version control, thorough documentation, and code review.
Train and mentor junior data analysts and research assistants in statistical methods, programming practices, and data management techniques.
Actively participate in research team meetings and scientific discussions, effectively present intermediate and final findings to both internal and external audiences.
Maintain a strong understanding of data governance policies, privacy regulations, and institutional review board (IRB) protocols.
Support continuous improvement of team workflows and contribute to the development of shared tools and resources for the research team.