Senior Data Analyst

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We have an exciting opportunity to join our team as a Senior Data Analyst. Dr. Sunita Desais' lab is seeking a qualified Senior Data Analyst with strong data management and programming skills, particularly in the use of large scale CMS administrative claims data and other large health care sets and the use of quasi-experimental research methods. Our teams work applies quantitative causal inference methods to large health care databases including health care claims, electronic health records, and all-payer discharge data to answer health policy/economics research questions.

Research projects address issues related to health care pricing, hospital markets, and the impacts of policies on health care spending and outcomes. The new team member will be responsible for data wrangling, analytic data set construction, and data analysis to support these projects and will ideally become involved and influential in decisions about the direction of the research and analysis.

Through this work, analysts will gain skills and knowledge in the practical implementation of causal inference, data analysis, health care policies and payment systems,/trends in health care policy and the delivery system. This role will work closely with Dr. Desai and other lab members to work on several federally funded initiatives. The individual in this position will support multiple projects in day-to-day activities which include data collection, preliminary data analysis, data visualization, and results dissemination.

The successful candidate will have a high degree of professional maturity, commitment to excellence, independence, flexibility, and initiative, and will possess the ability to work collaboratively with diverse individuals, teams, and populations both internally and externally.

• Wrangle, clean, and maintain data from large administrative claims data sets and other sources in support of research protocols and projects.
• Create secondary data sets from databases to support new and ongoing research.
• Perform reviews to ensure accuracy and completeness of data.
• Provide technical assistance and support to stakeholders to help them use data resources effectively and creatively.
• Under supervision of research faculty, conduct statistical analyses and present them to the team and collaborators.
• Support creation of tables and other data visualizations.
• Participate in project meetings and work groups to share knowledge and best practices.
• Produce publication ready tables and data visualizations.
• Think independently to identify data oddities, conceive of creative data visualizations, and suggest logical next steps.
• Contribute to team research project meetings.
• Perform other duties as assigned.

• Degree in economics, epidemiology, data science, biostatistics, health policy, or a related field.
• Interest in health policy/economics research and quantitative methods.
• Experience with advanced regression methods and causal inference methods (differences-in-differences, regression discontinuity, etc.).
• Comfort with handling large, relational data sets and working on servers.
• Highly proficient in R.
• Ability to perform fuzzy merges of complex data sets.
• Self-motivated and proactive with excellent organizational and communication skills.

• Experience working with administrative claims data and exposure to quasi-experimental econometric methods.
• Action-oriented and eager to embrace new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
• Comfortable working in a fast-paced environment.
• Strong organizational, prioritization, and time management skills.
• 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. 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. We offer financial security benefits, a generous time‑off program, employee resource groups, and a holistic employee…