Health Data Analyst

UHIN•Remote (UT, US), UT

1d•$72,000 - $85,000

About The Position

The Health Data Analyst (PHIG) assesses and improves health data quality, conducts advanced statistical analyses, and designs interactive reporting and visualization tools. Working across public health surveillance, clinical data, and claims databases, the analyst extracts complex datasets to support chronic disease monitoring, quality metrics, and population health initiatives. The role supports UHIN’s transition toward a data-driven culture through actionable insights, data governance, and regulatory compliance. The analyst performs data extraction, validation, cleaning, analysis, dashboard development, predictive modeling support, and stakeholder reporting. The role also supports research and survey projects, data-related inquiries, documentation, and cross-functional collaboration. There are no direct reports, though the position may manage projects.

Requirements

Bachelor’s degree in Healthcare Informatics, Epidemiology, Public Health, Data Analytics, Statistics, or a related field, or equivalent practical experience.
2–4 years of experience extracting, analyzing, interpreting, and reporting on complex healthcare and public health data.
Demonstrated experience working with healthcare claims and clinical datasets.
Hands-on experience with public health surveillance, chronic disease reporting, and population-level health analytics.
Experience assessing health data quality, accuracy, completeness, and timeliness across disparate systems.
Advanced SQL query development for complex data extraction, aggregation, and manipulation.
Experience with Python, including data visualization and statistical libraries.
Experience designing, developing, and maintaining interactive dashboards using BI tools such as Tableau or Power BI.
Proficiency with SQL, Python/R libraries, BI dashboards, statistical and research methods, and analysis of structured and unstructured quantitative and qualitative data.
Ability to identify complex problems, assess cost-benefit tradeoffs, perform quantitative and qualitative analyses, evaluate system performance metrics, and draw data-backed conclusions.
Strong verbal and written communication skills to explain complex findings and provide actionable recommendations to technical and non-technical stakeholders.
In-depth knowledge of HIPAA regulations and internal data governance policies, with the ability to maintain confidentiality, privacy, and security.
Strong time management, self-initiative, and prioritization skills; ability to lead meetings, manage projects, and collaborate across teams and with external stakeholders.

Nice To Haves

Master’s degree with specialized training in research methods and statistical analysis in a healthcare or public health domain, such as Informatics or Epidemiology.
Public health epidemiological experience.
Experience with machine learning algorithms, predictive analytics, and Natural Language Processing (NLP) for unstructured healthcare data.
Familiarity with R, JavaScript, Google BigQuery, and healthcare industry data standards.

Responsibilities

Write advanced, optimized SQL queries to aggregate and manipulate health data from internal and external clinical systems and claims databases.
Validate data integrity and conduct quality assurance and data cleaning across health records, public health registries, and insurance claims databases; coordinate with data contributors to resolve anomalies.
Design, develop, and maintain interactive BI tools such as Tableau and Power BI to track performance indicators, public health metrics, readmission rates, length of stay, and operational costs.
Conduct statistical analyses of patient and population data to identify chronic disease trends, track quality-of-care metrics, support public health surveillance, and inform hospital and community safety initiatives.
Develop, validate, and maintain statistical algorithms; collaborate with the Chief Data Officer to identify data requirements and provide clean datasets for predictive risk-scoring and resource-utilization models.
Translate complex findings into actionable recommendations for medical directors, clinicians, public health officials, and executive leadership.
Author research reports, technical specifications, process documentation, and training materials.
Maintain compliance with HIPAA, CMS regulations, and internal data governance policies across data extraction, storage, and reporting.
Plan, manage, and facilitate data projects, survey design studies, cross-functional meetings, and member/customer data inquiries.
Perform other duties as assigned.