Requirements

Job Overview

We are seeking a Programmer, Department of Health Management and Policy in the School of Health - Georgetown University with interests in the intersection of public health and big data. Applicants can hold a Master's degree in any data-related discipline and must have interest in conducting policy-relevant research that involves large data sets. The research fellow will work with Transformed Medicaid Statistical Information System (TAF) data and will help the team advance the research goals of an existing R01 grant. This is a full-time, temporary position. The appointment duration will be one-year with the potential for renewal.

The project investigates disparities in care among Medicaid beneficiaries with type 2 diabetes (T2DM) between 2016 and 2022. Medicaid covers 25% of Americans with T2DM. T2DM is burdensome and disproportionately impacts vulnerable and disenfranchised populations; of note, there are stark race/ethnic disparities in T2DM care goals, emergency department (ED) visits, and hospitalizations. States contract with private (non-profit or for-profit) Medicaid managed care organizations (MMCOs) to lower costs, increase quality, and pass on the financial risks of covering Medicaid beneficiaries. Heterogeneity across and within state programs can affect the quality of T2DM care and, specifically, disparities through benefit generosity or affecting MMCO entry and post-entry behavior. State policymakers also have significant influence over marketplaces where MMCOs compete, which can have consequences for race/ethnic disparities, given that Medicaid disproportionately covers non-white populations. We use data from the TAF representing over 86 million beneficiaries across all states, as well as all insurers, to provide policy-relevant insights into how Medicaid-managed care programs can be designed to reduce disparities in chronic disease burdens.

Additional duties include, but are not limited to:

• Analyze large datasets from CMS and other sources
• Construct tables and figures for publications and presentations
• Collaborate with PI on research questions and methodology
• Serve as data custodian for project and work with project manager on logistics
• Collaborate with researchers across different institutions

Work Interactions

The Programmer will work under the supervision of the PI, Maria Alva, PhD, and in cooperation with other project team members (including a graduate student data analyst and professor at a collaborating institution). The Programmer should be comfortable working independently, but they will have weekly meetings with the PI to review progress and adjust methodology as needed. They will also have a weekly meeting with the analyst from our collaborating institution and another with the data team. There will be monthly project team meetings during which the PI, programmer, collaborators, and project manager will discuss overall progress towards deliverables.

This position is situated in the Department of Health Management and Policy within the School of Health. The Department is a home for scholars and students to work collaboratively across disciplines and across the university to address human health and well-being from various perspectives - health care and health delivery systems, science, policy, law, economics, and the humanities - to achieve a deeper understanding of the interconnections among the most challenging issues of our time, and to find solutions.

Requirements and Qualifications

• Master-level degree or higher in data science, public policy, public health, economics, social sciences, computer science, or a related field with 7 to 8 years' experience.
• Familiarity with the following programming software: Python and SQL.

Please note: Only U.S. citizens, non-citizen nationals, or those lawfully admitted for permanent residence are eligible for this position.

Preferred Qualifications

• Prior experience working with Medicaid claims data would highly desirable.
• Previous experience working with Jupiter Notebooks and/or Github.
• Previous experience working in Databricks.

Work Mode Designation

This position has been designated as 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 positions can be found on the Department of Human Resources website: https://hr.georgetown.edu/mode-of-work-designation.

Pay Range:

The projected salary or hourly pay range for this position which represents the full range of anticipated compensation is:
$66,783.00 - $126,720.23

Compensation is determined by a number of factors including, but not limited to, the candidate's individual qualifications, experience, education, skills, and certifications, as well as the University's business needs and external factors.

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Submission Guidelines:

Please note that in order to be considered an applicant for any position at Georgetown University you must submit a resume for each position of interest for which you believe you are qualified. Documents are not kept on file for future positions.

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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.