Data Scientist

Vitality Living•Brentwood, TN

2d•Hybrid

About The Position

Vitality Living is a dynamic, hospitality-based senior housing owner and operator dedicated to delivering world-class service. We cultivate a culture that rewards initiative, values collaboration, and empowers team members to exceed expectations. Our success is rooted in hiring exceptional individuals who share our commitment to purpose-driven service, operational excellence, and continuous improvement. We are seeking a hands-on Data Scientist to build and deploy data-driven solutions across healthcare and senior housing operations. This role is responsible for developing, implementing, and maintaining statistical models, machine learning, and applied AI solutions to improve resident outcomes, optimize staffing and occupancy, enhance quality metrics, and support regulatory compliance. The ideal candidate combines deep technical expertise with healthcare domain knowledge and thrives in a build-and-execute environment. Hybrid Work Schedule: 2 days remote and 3 days in-office at our Support Office in Brentwood, TN.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, Biostatistics, or a related quantitative field
5+ years of hands-on experience in data science, including building and deploying models in production environments
Strong proficiency in Python or R for data analysis, model development, and production code
Advanced SQL skills and experience working with enterprise data warehouses and large-scale datasets, including data extraction, transformation, and performance-aware querying
Solid foundation in statistics, machine learning, applied AI, and predictive modeling
Experience working with sensitive or regulated healthcare data

Nice To Haves

Master’s degree in a quantitative or healthcare-related field
Experience in healthcare, senior housing, assisted living, or skilled nursing environments
Familiarity with healthcare data systems and standards (EHR/EMR, claims data, MDS, CMS quality metrics)
Experience with cloud platforms (AWS, Azure, or GCP)
Experience with data visualization tools (Tableau, Power BI, Looker)
Understanding of healthcare quality measures, regulatory reporting, and reimbursement models

Responsibilities

Analyze and validate clinical, operational, and financial data using advanced analytics and modeling techniques
Design, build, deploy, and maintain predictive and prescriptive models related to: Patient/resident outcomes (e.g., falls, readmissions, length of stay) Occupancy, census forecasting, and acuity trends Staffing optimization and labor cost management Quality measures and performance benchmarks
Apply statistical methods, machine learning, and AI techniques to develop production-ready solutions
Work within enterprise data warehouse environments to source, transform, and structure data for analytical and modeling purposes
Write production-quality code in Python or R for data pipelines, feature engineering, and model development
Partner with IT and data engineering teams to ensure scalable and reliable data pipelines and model deployment
Integrate and analyze data from multiple systems, including care management, CRM, procurement, and operational platforms
Build dashboards and reporting tools to support operational and clinical decision-making
Translate analytical outputs into clear, actionable recommendations
Ensure data integrity, privacy, and compliance with healthcare regulations (e.g., HIPAA)
Collaborate with clinicians, administrators, IT, and business teams to implement solutions
Mentor junior analysts or data scientists as needed