System Manager People Data Science

CommonSpirit Health was formed by the alignment of Catholic Health Initiatives (CHI) and Dignity Health. With more than 700 care sites across the U.S. from clinics and hospitals to home-based care and virtual care services CommonSpirit is accessible to nearly one out of every four U.S. residents. Our world needs compassion like never before. Our communities need caring and our families need protection. With our combined resources CommonSpirit is committed to building healthy communities advocating for those who are poor and vulnerable and innovating how and where healing can happen both inside our hospitals and out in the community.

The Manager, People Data Science leads the design, implementation, and evolution of a cutting-edge data architecture that enables the Talent, Learning & Capabilities function to deliver strategic, data-driven decision-making support. Leveraging expertise in advanced analytics, machine learning, and data visualization, this role entails technical leadership to guide the creation of impactful solutions that meet the needs of stakeholders across Human Resources and the broader organization.

As a key leader within the People Insights team, the Manager, People Data Science serves as the principal architect of the data science roadmap, ensuring alignment with organizational goals and leveraging modern tools and techniques to deliver predictive and prescriptive insights. This role collaborates heavily with researchers and the People Insights Products and Platforms team to enhance the maturity and robustness of solutions delivered. This role also provides mentorship and quality assurance across all advanced analytics efforts, fostering a data-driven culture and enabling actionable insights that address complex business challenges.

Key Responsibilities

• Defines, maintains and executes a forward-looking data architecture roadmap aligned with HR and organizational priorities.
• Identifies and prioritizes closing data gaps, ensuring scalability and integration with enterprise data platforms.
• Champions the use of emerging data science tools and technologies to optimize the insights function.
• Oversees the development of predictive and prescriptive models using techniques such as regression, machine learning (e.g., Random Forests, Gradient Boosting, Neural Networks), Structural Equation Modeling, and Path Analysis.
• Leads the application of advanced data science methodologies to create actionable insights, forecasts, and scenario simulations for HR leaders and key stakeholders.
• Stays ahead of industry trends, introducing innovations like generative AI and Natural Language Processing (NLP) to enhance data analysis capabilities.
• Translates complex analytics outputs into intuitive, actionable insights for decision-makers through dashboards, interactive tools, and storytelling.
• Provides supplemental documentation, training, and resources to empower leaders to make data-driven decisions effectively.
• Builds frameworks to enable predictive models to integrate seamlessly into HR processes and workflows.
• Manages and mentors data analysts and scientists, fostering a culture of innovation, collaboration, and continuous learning..
• Coordinates with external vendors and consultants to ensure high-quality data solutions and adherence to industry best practices.
• Ensures all analytics outputs are robust, accurate, and actionable by establishing and enforcing quality control protocols.
• Reviews and refines methodologies to ensure alignment with ethical and privacy considerations, particularly in people analytics.

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Industrial/Organizational Psychology, Finance, Human Resources, Business Administration, or a related field. A master’s degree or higher is strongly preferred.
• A minimum of 5 years of experience in data science, analytics, or related fields, with at least 1 year in a leadership, supervisory or team management role
• Proven expertise in advanced analytics and machine learning, with proficiency in R, Python, or equivalent programming languages.
• Experience in designing and implementing data architecture and operationalizing advanced analytics in a business environment.
• Strong knowledge of HR processes, workforce analytics, and business operations.Strong communication and interpersonal skills, with a demonstrated ability to present complex data in a clear and actionable manner to executives.
• A track record of staying ahead of emerging trends in data science, such as generative AI, NLP, and automated machine learning.