EnableComp provides Specialty Revenue Cycle Management solutions for healthcare organizations, leveraging over 24 years of industry-leading expertise and its unified E360 RCM™ intelligent automation platform to improve financial sustainability for hospitals, health systems, and ambulatory surgery centers (ASCs) nationwide. Powered by proprietary algorithms, iterative intelligence from 10M+ processed claims, and expert human-in-the-loop integration, EnableComp provides solutions across the revenue lifecycle for Veterans Administration, Workers’ Compensation, Motor Vehicle Accidents, and Out-of-State Medicaid claims as well as denials for all payer classes.Position SummaryThe Data Analyst responsibilities will include but not limited to quantitative analysis and predictive modeling of healthcare data to provide management with statistical findings and conclusions. The ideal candidate should be able to develop, collect and analyze metrics and data to formulate fact-based decisions and proactively implement process improvements through analysis of claim and operational data.Key ResponsibilitiesLead complex data analyses to identify trends, risks, and opportunities that support business decisions and operational improvementsDesign and develop advanced reports, dashboards, and analytical models to measure operational and financial performanceTranslate complex analytical findings into clear, concise, and executive-ready insights & recommendationsPartner with stakeholders to define analytical requirements and shape data-driven solutionsProactively identify areas for process improvement and drive recommendations based on data insightsBuild, validate, and maintain complex datasets, ensuring data accuracy, integrity, and consistencyWrite and optimize advanced SQL queries to extract, manipulate, and analyze large datasetsCollaborate with IT and data management teams to support data acquisition, integration, and system enhancementsSupport and help facilitate recurring reporting processes, including contributions to Quarterly Business Reviews (QBRs) and other leadership reportingApply critical thinking to diagnose root causes of issues and recommend scalable solutionsEnsure quality and reliability of all deliverables through rigorous validation and documentation of methodologiesDocument processes, logic, and assumptions to support transparency, repeatability, and knowledge transferManage multiple projects and priorities independently in a fast-paced, deadline-driven environmentProvide guidance and informal mentorship to junior analysts, supporting skill development and best practicesCommunicate effectively with both technical and non-technical audiences to drive understanding and alignmentAct as a trusted partner to stakeholders by effectively communicating insights to both technical and non-technical audiencesSupport continuous improvement initiatives through data analysis and performance monitoringMaintain working knowledge of business applications and support ongoing enhancements and optimizationStay current on analytics tools, methodologies, and industry trends to continuously improve capabilitiesOther duties as requiredRequirements and QualificationsBachelor’s degree in Analytics, Finance, Business, Computer Science, Healthcare Administration or other related field required4+ years of experience in SQL, data analysis, reporting, and working with relational databases required3 years of experience in healthcare, revenue cycle, or SaaS environment strongly preferredAdvanced proficiency in data extraction, transformation, and analysisFamiliarity with healthcare terminology (e.g., CPT codes, DRG, claims, inpatient/outpatient)Experience with BI tools such as Power BI, Tableau, or QlikExposure to statistical analysis or predictive modeling techniquesExperience supporting business reviews or executive-level reportingTimely and regular attendance.Equivalent combination of education and experience will be consideredTo perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Reasonable accommodations may be made to
