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Community Health Systems

Senior HCM Data Scientist - Remote

Posted Yesterday
In-Office or Remote
Hiring Remotely in United States
Senior level
In-Office or Remote
Hiring Remotely in United States
Senior level
Builds workforce analytics, visualizations, statistical analyses, time-series forecasts, and machine learning models using HR and clinical data. The role predicts staffing needs and employee attrition, analyzes pay and burnout relationships, supports pay equity and recruitment optimization, and translates HR strategies into measurable KPIs. Responsibilities include deploying models on cloud platforms, conducting experiments, protecting employee data, and communicating insights to technical and non-technical stakeholders.
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Our Benefits: 

Our team members enjoy a robust benefits package including:

  • Competitive compensation
  • Paid time off for vacations, holidays, and illness
  • Comprehensive health insurance (medical, dental, vision, prescription)
  • 401(k) retirement savings plan
  • Education support and student loan assistance
  • Life and disability insurance
  • Flexible spending account

Job Summary
This role is responsible for aligning the enterprise talent management strategy with operational data; building visualizations, statistical analyses, and predictive models to track progress and uncover areas for improvement. From forecasting nurse attrition to optimizing recruitment spend and ensuring pay equity, this role will use data sourced from Oracle HCM and other operational and clinical systems to drive the delivery of a best-in-class healthcare workforce.
Essential Functions

  • Collaborate with cross-functional teams including Human Resources (HR) and other operational leaders, data scientists, and software engineers to identify data-driven opportunities for enhancing human capital and operational processes.
  • Utilize cloud-based technologies, such as Google Cloud Platform (GCP), for scalable data processing and analysis.
  • Serve as the "Data Translator" for HR leadership, converting high-level people strategies (e.g., "reducing turnover by 15%") into specific analytical projects and KPIs.
  • Utilize Python programming and associated libraries such as PyTorch, Keras, Pandas and NumPY to create, train, test and implement meaningful data science models.
  • Create time-series models to predict future staffing needs based on seasonal patient volume, historical turnover, and local labor market trends
  • Develop and deploy machine learning models to identify "flight risk" employees, allowing leadership to intervene before high-value talent exits the organization.
  • Lead the analysis of multifactorial relationships, including those between premium pay (travelers/overtime) and employee burnout to provide recommendations on sustainable staffing and retainment models.
  • Collaborate with healthcare professionals and domain experts to understand operational needs and design data-driven solutions.
  • Design and conduct experiments, interpret results, and communicate findings to both technical and non-technical stakeholders

Qualifications

  • Bachelor's Degree in Data Science, Computer Science, Bioinformatics, or a related field required
  • Master's Degree preferred
  • Proficiency in Python programming and associated libraries.
  • Experience with cloud-based platforms such as Google Cloud Platform (GCP) for data storage, processing, and deployment.
  • 3–5 years of experience in People Analytics or HR Data Science, preferably within a large, complex organization (5,000+ employees).
  • Proven experience extracting and manipulating data from Oracle HCM Cloud, Workday, or SAP SuccessFactors.
  • Understanding of core HR functions: Talent Acquisition, Total Rewards, Employee Relations, and Learning & Development.
  • Deep understanding of data privacy laws (GDPR, CCPA) and the ethical implications of using AI in the employee lifecycle
  • Excellent communication and presentation skills with the ability to translate technical concepts to non-technical audiences.

Knowledge, Skills and Abilities

  • Advanced knowledge of machine learning techniques and statistical modeling approaches.
  • Proficiency in Python programming and associated libraries, including Scikit-learn, Keras, Pandas, NumPy, PyTorch, TensorFlow, and data visualization tools.
  • Experience developing and implementing natural language processing (NLP) solutions using tools such as spaCy, BERT, NLTK, or similar frameworks.
  • Knowledge of cloud computing platforms and experience deploying machine learning models in production environments.
  • Familiarity with containerization technologies such as Docker and Kubernetes.
  • Ability to analyze complex clinical datasets and translate findings into actionable insights.
  • Strong problem-solving skills with the ability to work independently and collaboratively in a fast-paced environment.
  • Excellent communication and presentation skills, with the ability to translate technical concepts to non-technical audiences.

This is a fully remote opportunity

This position is not eligible for immigration sponsorship now or in the future. Applicants must be authorized to work in the U.S. for any employer.

We know it’s not just about finding a job. It’s about finding a place where you are respected, valued and where your work is purposeful and fulfilling. A place where your talent is recognized, professional development is encouraged and career advancement is possible.

Community Health Systems is one of the nation's leading healthcare providers. With healthcare delivery systems in 36 distinct markets across 14 states, CHS operates 69 affiliated hospitals with more than 10,000 beds and approximately 1,000 other sites of care, including physician practices, urgent care centers, freestanding emergency departments, imaging centers, cancer centers, and ambulatory surgery centers.

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