Workforce Planning Data Scientist - Remote

Workforce Planning Data Scientist - Remote

The Workforce Planning Data Scientist will turn complex recruiting, staffing, workforce, and operational data into clear insights that enable better and faster business decisions.

This role blends data analytics, dashboard development, workforce forecasting, and foundational data engineering. The successful candidate will be comfortable working with large and complex datasets, reconciling information from multiple sources, developing scalable reporting solutions, identifying trends, and translating findings into practical recommendations for recruiting and workforce leadership.

While this is not a traditional Data Scientist or Data Engineer position, the role requires someone who can think beyond reporting what happened. The analyst should be able to determine why it happened, what is likely to happen next, and what actions should be considered as a result.

• Analyze workforce, recruiting, staffing, attrition, requisition, offer, start, and productivity data to identify trends, risks, and opportunities.
• Evaluate staffing performance across sites, business units, roles, and time periods.
• Analyze historical attrition patterns to identify where future hiring demand is likely to occur.
• Develop models and recommendations that help determine when and where requisitions should be opened proactively.
• Identify trends across weekly, monthly, quarterly, and historical workforce performance.
• Analyze relationships between staffing levels, attrition, hiring activity, requisition volume, recruiter productivity, and hiring outcomes.
• Conduct ad hoc analyses in response to evolving workforce and leadership priorities.

• Build workforce forecasts incorporating staffing requirements, active headcount, attrition, projected starts, hiring velocity, and historical trends.
• Identify emerging staffing risks before they materially impact operations.
• Develop scenario analyses to evaluate different hiring and attrition assumptions.
• Identify leading indicators that can improve workforce planning and recruiting decisions.
• Assess whether workforce and recruiting performance is trending toward or away from established targets.

• Design and maintain intuitive dashboards that translate complex datasets into clear, actionable information.
• Develop reporting for staffing health, recruiter productivity, requisition aging, time to offer, hiring outcomes, attrition, projected starts, and workforce demand.
• Create leadership level views that allow users to quickly understand performance, risks, trends, and required actions.
• Continuously improve dashboards based on business needs and user feedback.

• Work with multiple data sources and large datasets that may contain hundreds of thousands to millions of records.
• Clean, transform, combine, and structure data for analysis and reporting.
• Understand data pipelines, relationships, joins, data models, and source/system dependencies.
• Partner with Data Engineering and BI resources on more complex data architecture and pipeline requirements.
• Automate repeatable reporting and data preparation processes when practical.
• Troubleshoot data inconsistencies and reconcile conflicting numbers across systems

• Validate and reconcile workforce metrics before they are used for business decisions.
• Identify data quality issues, missing information, duplicate records, inconsistent definitions, and source/system discrepancies.
• Establish clear metric definitions and calculation logic.
• Ensure leadership reporting is consistent, repeatable, and explainable.

What You'll Need:

• Bachelor's Degree preferred with 5 plus years of relevant experience in talent acquisition analytics, workforce planning, or people analytics. In lieu of a degree, a combination of experience and education will be considered.
• Demonstrated experience analyzing complex, high volume datasets.
• Strong experience developing dashboards and executive level reporting.
• Experience performing trend analysis, forecasting, and scenario modeling.
• Demonstrated ability to reconcile data across…