People Data Scientist

Benefits

Additional Information

The People Data Scientist applies advanced statistical, analytical, and data science methodologies to workforce and organizational data to generate actionable insights that support talent and business decisions. This role leverages predictive modeling, experimentation, machine learning, and workforce analytics to identify trends, assess organizational effectiveness, and inform strategies related to talent acquisition, employee engagement, retention, performance, workforce planning, and diversity initiatives. Working collaboratively with Human Resources, Talent Acquisition, Total Rewards, Learning and Development, Finance, and business leaders, the People Data Scientist translates complex workforce data into meaningful recommendations and decision-support tools. The position develops predictive models, conducts research and experimentation, and delivers data-driven insights that improve organizational performance while ensuring ethical, responsible, and compliant use of employee data. Job Responsibilities: Serve as a subject matter expert for HR technology, workforce data, and people analytics, supporting the optimization and effective use of HCM systems and reporting solutions. Facilitate and support HCM system implementations, enhancements, integrations, testing, and ongoing system optimization across HR, Payroll, Benefits, Talent, and Workforce Management functions. Partner with HR, Finance, IT, Payroll, and business leaders to gather requirements, improve processes, and implement scalable workforce technology and analytics solutions. Configure and maintain HRIS workflows, security roles, business processes, system controls, and reporting structures to support operational efficiency and data integrity. Manage workforce data governance activities, including data validation, audits, compliance monitoring, and the maintenance of accurate and reliable employee data across multiple systems. Develop workforce analytics and statistical analyses to identify trends, correlations, and actionable insights related to headcount, turnover, retention, recruiting, labor costs, engagement, diversity, and workforce planning. Apply predictive analytics, forecasting techniques, and data modeling methodologies to support strategic workforce planning and organizational decision-making. Design, develop, and maintain dashboards, scorecards, and executive reporting solutions that provide visibility into key workforce and business metrics. Translate complex workforce data into clear visualizations, executive presentations, and data-driven narratives that connect people's metrics to business outcomes. Create and maintain automated reporting processes, data integrations, and data pipeline solutions that improve efficiency, accuracy, and scalability of workforce reporting. Partner with HR Centers of Excellence, including Talent Acquisition, Total Rewards, Learning and Development, and Employee Relations, to support analytical and reporting needs. Identify opportunities to improve workforce processes, reporting capabilities, and HR technology solutions through data analysis, automation, and emerging technologies, including AI-enabled tools. Education, Experience, Knowledge, Skills and Abilities: Bachelor's degree in data science, Statistics, Mathematics, Economics, Industrial-Organizational Psychology, Computer Science, Analytics, Business, Human Resources, or a related quantitative field required; Master's degree preferred. Minimum of 5 years of experience in data science, people analytics, workforce analytics, applied research, or a related analytical discipline. Strong knowledge of statistical modeling, predictive analytics, machine learning, hypothesis testing, survey methodology, and experimental design. Proficiency in SQL and at least one analytical programming language such as Python or R. Experience working with business intelligence and data visualization tools to develop dashboards, reports, and executive presentations. Demonstrated ability to analyze large and complex datasets and communicate findings to diverse audiences. Knowledge of workforce analytics, organizational research methods, employee lifecycle metrics, and talent management concepts preferred. Strong critical thinking, problem-solving, and analytical skills with the ability to independently manage complex projects and priorities. Understanding of data governance, data privacy, responsible AI practices, and bias mitigation principles. Excellent communication and consulting skills with the ability to influence decisions through data-driven insights and recommendations.

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