MCH Health Care Data Analyst

Job Responsibilities

• Provides high-level professional healthcare claims analytics work related to Medicaid.
• Conducts quantitative analyses that support health care projects and research activities focused on Maternal and Child Health (MCH) populations.
• Utilizes database technologies to acquire, transform, and standardize data to power dashboards and reports.
• Gathers, analyzes, and compiles healthcare and provider data to develop and evaluate MCH programs and policies.
• Works collaboratively as a part of an interdisciplinary team, including researchers, policy analysts, biostatisticians, data scientists, and data visualization specialists to address analytic needs and strategic priorities.
• Conducts research, evaluation, and policy analysis to improve MCH outcomes and strengthen health care and delivery systems serving women, infants, children, and families.

Requirements

• Experience/training in health services research.
• At least 4 years of experience with the analysis of claims/encounter data.
• Strongly prefer an understanding of Medicaid, Medicare, and/or private healthcare claims data systems.
• Understanding of and/or experience with analysis of electronic health record data, including data elements used in MCH contexts.
• Strong proficiency in SAS, SQL, R, and Python.
• Knowledge/Skills/Abilities: Strong analytical thinking and attention to detail; experience with large relational database administration; demonstrated experience in data management and analysis with administrative data, including health or behavioral healthcare claims such as Medicaid, Medicare, private insurance data, or state agency and national datasets; experience with relevant MCH populations preferred; proficiency in SAS, SQL, and other statistical analytical software programs (e.g., R, Python); demonstrated ability to use analytical and visualization tools such as Excel (including advanced data manipulation techniques) and Power BI; interest in public health or issues relevant to health services research, MCH, and health program or policy evaluation; ability to plan for and work on multiple projects concurrently; ability to exercise sound judgment in making decisions and maintain thorough documentation of the decision-making process; exemplary communication skills and ability to communicate effectively, both verbally and in writing, complicated processes to diverse audiences; strong commitment to rigorous research methods, objectivity, accuracy of findings, and reproducibility of results.

Qualifications

Preferred Qualifications: Experience/training in health services research. At least 4 years of experience with the analysis of claims/encounter data. Strongly prefer an understanding of Medicaid, Medicare, and/or private healthcare claims data systems. Understanding of and/or experience with analysis of electronic health record data, including data elements used in MCH contexts. Strong proficiency in SAS, SQL, R, and Python. Knowledge/Skills/Abilities: Strong analytical thinking and attention to detail. Experience with large relational database administration. Demonstrated experience in data management and analysis with administrative data, including health or behavioral healthcare claims such as Medicaid, Medicare, private insurance data, or state agency and national datasets; experience with relevant MCH populations preferred. Proficiency in SAS, SQL, and other statistical analytical software programs (e.g., R, Python). Demonstrated ability to use analytical and visualization tools such as Excel (including advanced data manipulation techniques) and Power BI. Interest in public health or issues relevant to health services research, MCH, and health program or policy evaluation. Ability to plan for and work on multiple projects concurrently. Ability to exercise sound judgment in making decisions and maintain thorough documentation of the decision-making process. Exemplary communication skills and ability to communicate effectively, both verbally and in writing, complicated processes to diverse audiences. Strong commitment to rigorous research methods, objectivity, accuracy of findings, and reproducibility of results.

Pay

TBD

Schedule

Full Time

Benefits

N/A