Flex Staff - By Hour, FTE 0.27, Emergency Medicine

Job Description

Strength Through Diversity

Ground breaking science. Advancing medicine. Healing made personal.


Perform data management and analysis activities on large secondary data sources. Working with the Population Science Research Group (PSR), develop a data management system for multiple years of health services claims and administrative data. Sources will include, but not be limited to, data from the Centers for Medicare & Medicaid Services and the Healthcare Cost & Utilization Project from the Agency for Healthcare Research & Quality. This work will support the PSR’s work to benchmark risk-adjusted hospital and regional outcomes. In addition, this position will work closely with experts in machine learning to explore the use of these methods to describe previously unrecognized patterns that data reveals.


Roles & Responsibilities:

  • Use multiple data sources to provide a comprehensive and rigorous assessment of the potential for innovative approaches to service delivery and payment models to improve health outcomes and reduce spending for Medicare
  • Perform data management activities on large secondary databases
  • Assemble analytic datasets for internal and external collaborators at direction of principal investigator and research team • Write new program code using prescribed specifications and maintain programming documentation, document programming problems and resolutions for future reference
  • Perform data analysis activities in conjunction with, and/or under the supervision of research team, including but not limited to descriptive statistics, regression models (hierarchical, time to event), spatial clustering, and machine/deep learning
  • Contribute to academic manuscripts, with emphasis on creation of tables and figures to display results; expertise in describing statistical methods and statistical results preferred
  • Maintain high standards for data management, quality, reporting, and timely project execution
  • Education: Bachelor’s degree required. Master’s Degree in related field preferred. Prior experience in data management and analysis required
  • Experience: Prior experience working in a health care delivery or health policy focused setting preferred

Strength Through Diversity


The Mount Sinai Health System believes that diversity is a driver for excellence. We share a common devotion to delivering exceptional patient care. Yet we’re as diverse as the city we call home- culturally, ethically, in outlook and lifestyle. When you join us, you become a part of Mount Sinai’s unrivaled record of achievement, education and advancement as we revolutionize medicine together.


We work hard to acquire and retain the best people, and to create a welcoming, nurturing work environment where you can develop professionally. We share the belief that all employees, regardless of job title or expertise, can make an impact on quality patient care. 


Explore more about this opportunity and how you can help us write a new chapter in our story! 

Who We Are

Over 38,000 employees strong, the mission of the Mount Sinai Health System is to provide compassionate patient care with seamless coordination and to advance medicine through unrivaled education, research, and outreach in the many diverse communities we serve.


Formed in September 2013, The Mount Sinai Health System combines the excellence of the Icahn School of Medicine at Mount Sinai with seven premier hospital campuses, including Mount Sinai Beth Israel, Mount Sinai Beth Israel Brooklyn, The Mount Sinai Hospital, Mount Sinai Queens, Mount Sinai West (formerly Mount Sinai Roosevelt), Mount Sinai St. Luke’s, and New York Eye and Ear Infirmary of Mount Sinai.


The Mount Sinai Health System is an equal opportunity employer. We comply with applicable Federal civil rights laws and does not discriminate, exclude, or treat people differently on the basis of race, color, national origin, age, religion, disability, sex, sexual orientation, gender identity, or gender expression. 


EOE Minorities/Women/Disabled/Veterans



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