Analytics Analyst III ON-SITE Woodard

Analytics Analyst III - (ON-SITE) Woodard, (1568)

Scheduled Shift: Monday-Friday  and other shifts as needed.

This position requires on-site training and attendance during the initial onboarding period. Applicants must be able to reliably commute to the work location and participate in all in-person training sessions. Only candidates who meet these requirements will be considered.

The Analytics Analyst III is an experienced analyst who independently performs complex data analysis, develops dashboards, and delivers actionable insights. This role translates business needs into analytical solutions and supports decision-making across functional areas. The role helps develop reporting and analytics solutions, translates complex data into clear audience-appropriate insights, and serves as a data steward to maintain reliable analytics foundations.

• Collaborate with stakeholders to define requirements, KPIs, and business questions.
• Generate insights and recommendations to support operational and financial decisions.
• Design and develop SQL queries, datasets, and intermediate data models.
• Perform advanced analysis including trend analysis, segmentation, and root cause analysis.
• Develop dashboards and report solutions aligned to business needs.
• Lead small-to-medium analytics efforts from design through delivery and reporting consistency.
• Manage scope, timelines, and stakeholder expectations for ad-hoc and standard deliverables.
• Assist with maintaining data stewardship and analytical foundations (data marts, definitions).
• Collaborate with IT/data engineering to improve pipelines data ecosystems
• Ensure data quality, consistency, and KPI alignment.
• Other related duties as assigned.

Bachelor’s degree in quantitative or technical field such as data analytics, computer science, information systems, finance or related discipline required.

3–5+ years of experience in analytics, reporting, business intelligence, or data-related roles.

• Experience with healthcare data (claims, EHR, clinical, financial datasets or revenue cycle) or clinical laboratory environment.
• Understanding of healthcare systems, reimbursement models, and regulatory requirements (e.g., Medicare, Medicaid, HIPAA).
• Experience working with data warehouse environments.
• Experience with data modeling and data quality best practices.