Remote Workforce Data Scientist & Forecasting

RemoteFetch; Atlanta (GA); Remote; USD 110,000 - 150,000; Full time

Job summary

CBRE is seeking a Workforce Planning Data Scientist to transform recruiting, staffing, and operational data into clear insights for faster decision-making.

The role blends analytics, dashboard development, workforce forecasting, and foundational data engineering. You will work with large datasets, reconcile sources, and translate findings into practical recommendations for workforce leadership.

Qualifications

• Bachelor's degree preferred with 5+ years in talent analytics, workforce planning, or people analytics.
• Experience analyzing large, high-volume datasets.
• Strong dashboard and executive-level reporting experience.
• Forecasting, scenario modeling, and trend analysis experience.
• Ability to reconcile data across multiple systems and resolve quality issues.
• Translate complex analyses into actionable business recommendations.

Responsibilities

• Analyze workforce, recruiting, attrition, requisition, and productivity data to identify trends and risks.
• Evaluate staffing performance across sites, units, and time periods.
• Develop workforce forecasts and proactive requisition recommendations.
• Build dashboards for staffing health, recruiter productivity, and hiring outcomes.
• Design leadership views to summarize performance, risks, and actions.
• Partner with data engineering and BI to optimize data pipelines and data quality.

Skills

SQL

Excel

Power BI

Python (Pandas/NumPy)

ETL/ELT

Data modeling

Cloud data environments

APIs

ATS/HRIS knowledge

Forecasting & scenario modeling

Education

Bachelor's Degree

Tools

SQL

Excel

Power BI

Python (Pandas/NumPy)

ETL/ELT

Job description

CBRE is seeking a Workforce Planning Data Scientist to transform recruiting, staffing, and operational data into clear insights for faster decision-making.

The role blends analytics, dashboard development, workforce forecasting, and foundational data engineering. You will work with large datasets, reconcile sources, and translate findings into practical recommendations for workforce leadership.