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Data Analyst - Emergency MedicineColumbia UniversityNew York, New York, United States

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Data Analyst - Emergency Medicine

Columbia University
  • US
    New York, New York, United States
  • US
    New York, New York, United States

Über

Job Type: Officer of Administration
Regular/Temporary: Regular
Hours Per Week: 35
Salary Range: $70,000 - $90,000
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.
Position Summary
POSITION SUMMARY
The Emergency Department at Columbia University has a diverse portfolio of internal and externally funded clinical and epidemiological research with a strong focus on data science. We are seeking an enthusiastic and creative data analyst to join our team of research investigators. The data analyst will work on research projects employing latent variable modeling and risk prediction methods to better understand substance use related morbidity and mortality outcomes (e.g., overdose, hospitalization). This position is ideal for someone with a strong background in applied statistics, epidemiology, or data science, and passion for working with public health challenges involving substance use and behavioral health. Reporting to Raquel Shrager, Director and Dr. Kechna Cadet (Principal Investigator), the Data Analyst will be responsible for preparing, developing, and presenting analytic solutions for the wide breadth of research in the Department of Emergency Medicine. This is a dynamic role, in which the Data Analyst will work closely with the Principal Investigator to guide study design, database creation, management, and analysis.
Responsibilities
PRINCIPAL RESPONSIBILITIES
Analyze complex datasets involving substance use behaviors, health outcomes, and sociodemographic factors
Develop and validate predictive models for morbidity and mortality risk
Work with structured and unstructured data from multiple sources (e.g., electronic health records, surveys, administrative datasets)
Interpret findings and communicate results via manuscript writing and presentations
Develop dashboards to report requested data sets to varying audiences and for the portfolio of epidemiological research studies
Help create and maintain research databases with guidance and direction from Principal Investigators
Remain abreast and updated of NYP and CUMC mandates, provide data and metrics to comply as needed
Serve as departmental liaison to Medical Center and University for data science related matters
For externally funded programs, lead Pre-award requests for arranging data in preparation of grant applications
Post-award (funded studies) responsibilities include preparing data progress reports, general statistics and demographics to be disseminated to the Principal Investigators and sponsors
Minimum Qualifications
Requires a bachelor's degree or equivalent in education and experience; plus, three years of related experience.
Preferred Qualifications
Master's degree preferred in epidemiology, data science, biostatistics, public health, or related field, plus at least two years directly related experience required.
Advanced knowledge and proficiency in statistical programming (e.g., R, SAS, Python, Stata) preferred; prior experience with Tableau, and/or Epic preferred; working knowledge of MPLUS and SQL is a plus.
Must possess excellent interpersonal and communication skills; a professional and positive can do attitude is a must. Adept at solving problems quickly, efficiently, and independently.
Must be able to communicate, both verbally and in writing, in a professional and succinct manner, and be open to feedback and collaboration.
Equal Opportunity Employer / Disability / Veteran
Columbia University is committed to the hiring of qualified local residents.
  • New York, New York, United States

Sprachkenntnisse

  • English
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