Data Scientist

Hospice-of-Michigan; Ann Arbor (MI); On-site; USD 90,000 - 120,000; Full time

Job summary

Hospice-of-Michigan is seeking a data analytics professional to lead the analysis, modeling, and reporting of clinical, operational, financial, and administrative data to support patient care, quality improvement, regulatory compliance, and organizational decisions.

You will develop statistical and predictive models for census, length of stay, utilization, and staffing; maintain dashboards for clinical and executive leadership; ensure HQRP submissions and other regulatory requirements; translate

Qualifications

• Analyzing and modeling data to support patient care, quality improvement, regulatory compliance, and organizational decision-making.
• Maintaining dashboards and reporting tools for clinical and executive leadership.
• Translating data findings into actionable recommendations for care delivery and staffing.

Responsibilities

• Develop statistical and predictive models related to patient census, length of stay, utilization, staffing, and other organizational needs.
• Maintain dashboards and reporting tools for clinical and executive leadership.
• Support HQRP submissions and other regulatory requirements.
• Serve as liaison between analytics and clinical/operational teams to drive care improvements.

Job description

This position is responsible for the analysis, modeling, and reporting of clinical, operational, financial, and administrative data to support patient care, quality improvement, regulatory compliance, and organizational decision-making across the organization. Core functions include developing statistical and predictive models related to patient census, length of stay, utilization, staffing, and other organizational needs; maintaining dashboards and reporting tools for clinical and executive leadership; and supporting CMS Hospice Quality Reporting Program (HQRP) submissions and other regulatory requirements.

The role serves as a liaison between the analytics function and clinical/operational teams, translating data findings into actionable recommendations for care delivery, staffing, and program planning. Given the sensitivity of the patient population served, this position requires strict adherence to data privacy standards and a consistently thoughtful approach to the handling and presentation of patient-level data.