Senior Data Analyst

University of Arkansas for Medical Sciences•Little Rock, AR

22h

About The Position

The Arkansas Center for Health Improvement (ACHI) is a health policy organization that is administratively housed within the University of Arkansas for Medical Sciences. ACHI's mission is to be a catalyst for improving the health of Arkansans through evidence-based research, public issue advocacy, and collaborative program development. The Senior Data Analyst will be part of a dynamic team contributing to and providing internal leadership on analytic research projects for ACHI’s policy efforts. In collaboration with the Director of Analytics, the Assistant Director of Analytics, principal investigators, and other ACHI staff, the Senior Data Analyst will develop and implement advanced data and statistical analytics using private and public healthcare claims data and other health data to inform research on important health policy questions, as well as cost and quality comparative studies for the State of Arkansas. The position requires the ability to manipulate medical claims data, including data from an all-payer claims database, multiple large public and private health data sources, and numerous other data sources.

Requirements

Bachelor’s Degree plus 5 years of experience in analytics, health services research, statistics, mathematics, computer science, health policy/economics or related field OR Master’s Degree plus 3 years of experience in analytics, health services research, statistics, mathematics, computer science or health policy/economics or related field
Manipulation of large datasets using statistical programming or advanced data management software, such as such as SAS and SQL; experience using SAS is required and both would be preferred.
Use of advanced SAS functions to manipulate data to create time dependent analytical variables
Use of statistical techniques, including univariate statistics, comparisons, and regression modeling
Application, calculation, and interpretation of descriptive and inferential data
Traits and Abilities in the following areas are required: Self-motivated to learn and explore new and existing ideas. Think critically and strategically. Work well independently and in a team environment. Manage and prioritize multiple tasks/projects. Work efficiently and meet deadlines. Communicate well both verbally and in writing.

Nice To Haves

Health care utilization and cost analyses
Knowledge and use of national data sources (e.g., ACS, HCUP, MEPS)
Health services research, such as health care quality, Medicaid eligibility, Medicaid/Medicare claims, health disparities, or chronic diseases
ICD-9/10 Diagnosis, ICD-9/10 Procedure, CPT, HCPCS, DRG/MS-DRG, NDC, Type of Service, Place of Service and other codes commonly utilized in health care data sets
Knowledge of ArcGIS or other geographical coding programs to assist in health geocoding/mapping

Responsibilities

Statistical Programming and Analyses Develop complex and efficient data analytic and statistical programs to manipulate healthcare data to create research-ready datasets for empirical analyses.
Import and longitudinally cross-link data from a variety of sources to develop research-ready analytic datasets.
Import and integrate large, complex datasets using SAS, including administrative claims data and enrollment files from a variety of insurance payers.
Execute basic descriptive and inferential statistical analyses.
Collaboration Communicate and collaborate with the Director of Research and Evaluation and the Assistant Director of Analytics on translating policy questions into initial analytic plans based on policy questions.
Communicate and collaborate with project teams made up of other staff who possess data, policy, and other skillsets.
Technical Writing Create written data analytic plans with detailed data management procedures to transform raw healthcare data into research-ready analytic datasets.
Write methodological components of technical reports following accepted protocols.
Maintain detailed programming documentation for all projects, including annotated program code, dataset codebooks, and statistical output.
Research Identify relevant background information to inform analytic plans designed to answer policy-related questions.
Identify new techniques and approaches to enhance current or future analytic reporting.