Data Analyst at NYU Langone Health in New York, NY
Position
Summary:
We have an exciting opportunity to join our team as a Data Analyst. The Brooklyn Data Station at NYU Grossman School of Medicine Department of Population Health provides a one-stop resource for researchers from Population Health and Family Health Centers at NYU Langone to come for assistance accessing, analyzing and communicating clinical and population-based data most relevant to the communities served by the Family Health Centers. The Brooklyn Data Station also supports the work of the Community Service Plan by providing local data for needs assessments, quality improvement and program development. The Data Analyst will join the Brooklyn Data Station team and will work closely with faculty and staff to analyze and summarize clinical data from electronic health records and other administrative, survey and program-specific datasets. The Data Analyst will co-report to DataCore, MCIT Research and Education and follow the best practice and governance on handling electronic health records. Job
Responsibilities:
Serve as a data analyst to support Brooklyn-focused programs, and other population health initiatives, using a range of data sources including:
Electronic health records (NYU Epic); Community-based health and demographic surveys; Project-specific surveys and assessments; Administrative records (births, education, Medicaid claims); Other novel data sources. Lead data management and analytic processes:
Write queries to extract data from electronic health records; Integrate data from multiple sources, including electronic health records, published literature, surveys, censuses, administrative records, vital registration systems, and disease registries; Innovate and streamline ways to bring together and visualize data; Develop and document code that can be used by a diverse range of individuals to solve commonly encountered problems and implement widely used analyses; Develop routine reports for project monitoring; Create and maintain data dictionaries and other metadata resources to share with other analysts and researchers; Work with faculty and staff to respond to their requests for clinical data; Understand and follow all data security requirements; Provide technical assistance and support to stakeholders to help them use data resources effectively and creatively; Participate in project meetings and workgroups to share knowledge and best practices. Lead and/or support scientific publications; support grant proposal submissions; support funder reports:
Analyze and summarize data; Create text, tables, figures, and charts for presentations and publications for scientific and community audiences; Create effective forms of data visualization, tailored to program and stakeholder needs; Execute queries on databases to respond to the needs of partners and external requests from collaborators, policymakers, donors, and other stakeholders. Minimum
Qualifications:
To qualify you must have a Masters in epidemiology, data science, public health or related field and 2-3 years of experience in data management; Demonstrated success in developing code in SAS, R, SQL, Python, Stata or other coding language; Demonstrated facility with analytic tasks and ability to participate productively in interdisciplinary research teams; Strong quantitative aptitude, desire to learn new skills and information, and ability to interpret complex analytic quantitative information; Strong attention to detail; Demonstrated organizational skills, self-motivation, flexibility, strong communication skills, and the ability to thrive in a fast-paced, energetic, highly creative, entrepreneurial environment. Preferred
Qualifications:
Masters degree in pertinent field (clinical informatics; information management, biostatistics, epidemiology, public health, health care administration or similar field). Experience with Hadoop and/or SQL are preferred. Skills and Specifications:
Familiarity with clinical information, including diagnostic coding and clinical databases. Knowledge of principles and methods of biostatistics; principles, theories, and procedures of epidemiology, including study design, statistical analysis, and causal inference. Knowledge of current research and trends in public health; appropriate computer processing methods used to generate, organize and display statistical and research data; and standard English grammar, spelling, and usage. Ability to apply mathematical formulas and make calculations. Ability to gather, organize, analyze, and report findings from analyses. Problem-solving skills. Planning/organizational skills. Personal motivation. Knowledge of Chinese (Mandarin or Cantonese) or Spanish preferred. 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.
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
Summary:
We have an exciting opportunity to join our team as a Data Analyst. The Brooklyn Data Station at NYU Grossman School of Medicine Department of Population Health provides a one-stop resource for researchers from Population Health and Family Health Centers at NYU Langone to come for assistance accessing, analyzing and communicating clinical and population-based data most relevant to the communities served by the Family Health Centers. The Brooklyn Data Station also supports the work of the Community Service Plan by providing local data for needs assessments, quality improvement and program development. The Data Analyst will join the Brooklyn Data Station team and will work closely with faculty and staff to analyze and summarize clinical data from electronic health records and other administrative, survey and program-specific datasets. The Data Analyst will co-report to DataCore, MCIT Research and Education and follow the best practice and governance on handling electronic health records. Job
Responsibilities:
Serve as a data analyst to support Brooklyn-focused programs, and other population health initiatives, using a range of data sources including:
Electronic health records (NYU Epic); Community-based health and demographic surveys; Project-specific surveys and assessments; Administrative records (births, education, Medicaid claims); Other novel data sources. Lead data management and analytic processes:
Write queries to extract data from electronic health records; Integrate data from multiple sources, including electronic health records, published literature, surveys, censuses, administrative records, vital registration systems, and disease registries; Innovate and streamline ways to bring together and visualize data; Develop and document code that can be used by a diverse range of individuals to solve commonly encountered problems and implement widely used analyses; Develop routine reports for project monitoring; Create and maintain data dictionaries and other metadata resources to share with other analysts and researchers; Work with faculty and staff to respond to their requests for clinical data; Understand and follow all data security requirements; Provide technical assistance and support to stakeholders to help them use data resources effectively and creatively; Participate in project meetings and workgroups to share knowledge and best practices. Lead and/or support scientific publications; support grant proposal submissions; support funder reports:
Analyze and summarize data; Create text, tables, figures, and charts for presentations and publications for scientific and community audiences; Create effective forms of data visualization, tailored to program and stakeholder needs; Execute queries on databases to respond to the needs of partners and external requests from collaborators, policymakers, donors, and other stakeholders. Minimum
Qualifications:
To qualify you must have a Masters in epidemiology, data science, public health or related field and 2-3 years of experience in data management; Demonstrated success in developing code in SAS, R, SQL, Python, Stata or other coding language; Demonstrated facility with analytic tasks and ability to participate productively in interdisciplinary research teams; Strong quantitative aptitude, desire to learn new skills and information, and ability to interpret complex analytic quantitative information; Strong attention to detail; Demonstrated organizational skills, self-motivation, flexibility, strong communication skills, and the ability to thrive in a fast-paced, energetic, highly creative, entrepreneurial environment. Preferred
Qualifications:
Masters degree in pertinent field (clinical informatics; information management, biostatistics, epidemiology, public health, health care administration or similar field). Experience with Hadoop and/or SQL are preferred. Skills and Specifications:
Familiarity with clinical information, including diagnostic coding and clinical databases. Knowledge of principles and methods of biostatistics; principles, theories, and procedures of epidemiology, including study design, statistical analysis, and causal inference. Knowledge of current research and trends in public health; appropriate computer processing methods used to generate, organize and display statistical and research data; and standard English grammar, spelling, and usage. Ability to apply mathematical formulas and make calculations. Ability to gather, organize, analyze, and report findings from analyses. Problem-solving skills. Planning/organizational skills. Personal motivation. Knowledge of Chinese (Mandarin or Cantonese) or Spanish preferred. 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.
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
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