Data Analyst (temporary, part-time) - Health Data Analytics Program - Georgetown University
Georgetown University
Application
Details
Posted: 11-May-23
Location: Washington, D.C.
Type: Part-time
Salary: Open
Internal Number: 4177991
Data Analyst (temporary, part-time) - Health Data Analytics Program - Georgetown University
Located in a historic neighborhood in the nation's capital, Georgetown offers rigorous academic programs, a global perspective, exciting ways to take advantage of Washington, D.C., and a commitment to social justice. Our community is a tight knit group of remarkable individuals interested in intellectual inquiry and making a difference in the world.
Requirements
Data Analyst (temporary, part-time) - Health Data Analytics Program - Georgetown University
Job Overview
The Data Analyst - in a temporary, part-time role - plays an integral supporting role in the Health Data Analytics Program in the Office of the Senior Vice President for Research.
Working closely with clients, such as health department jurisdictions nationwide, they gather information regarding the functionality requirements for the ATra Black Box in responsibilities that include but are not limited to:
Maintain documentation of critical Black Box requirements
Provide recommendations to the project team based on client feedback
Assist in the development of schematics of software rules, logic, and data processing/analytic components
Work Interactions
Reporting to the Director, Health Data Analytics Program, the Data Analyst works internally with several staff and faculty in the Office of the Senior Vice President for Research and the Health Data Analytics Program, including the Senior VP for Research, Program Director, Project Manager(s), co-PIs (faculty members), the Computational Research Specialist (programmer), and UIS partners.
As well, they routinely work with external clients (nationwide health department jurisdictions) and Oak Ridge National Lab partners.
Qualifications
Bachelor's degree - preference for Master's degree in public health with epidemiology concentration or related fields - in particular data science, data analytics, computer science
3 years relevant experience
Knowledge of epidemiology and disease surveillance principles
Excellent verbal and written communication skills.
Experience working with large datasets and relational databases (ability to understand how the various source datasets are internally and externally related to one another)
Understanding of data structures, formatting, and standardization processes
Work Mode: Hybrid. Please note that work mode designations are regularly reviewed in order to meet the evolving needs of the University. Such review may necessitate a change to a position's mode of work designation. Complete details about Georgetown University's mode of work designations for staff and AAP positions can be found on the Department of Human Resources Mode of Work Designation.
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EEO Statement:
Georgetown University is an Equal Opportunity/Affirmative Action Employer fully dedicated to achieving a diverse faculty and staff. All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, color, religion, national origin, age, sex (including pregnancy, gender identity and expression, and sexual orientation), disability status, protected veteran status, or any other characteristic protected by law.
Benefits:
Georgetown University offers a comprehensive and competitive benefit package that includes medical, dental, vision, disability and life insurance, retirement savings, tuition assistance, work-life balance benefits, employee discounts and an array of voluntary insurance options. You can learn more about benefits and eligibility on the Department of Human Resources website.
Established in 1789, Georgetown is the nation's oldest Catholic and Jesuit University. Georgetown is one of the world's leading academic and research institutions, offering a unique educational experience that prepares the next generation of global citizens to lead and make a difference in the world.