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We are seeking a highly analytical and data-driven Capacity Planning Analyst to optimize workforce and operational resources alignment with current and future business demands. This role leverages advanced data science techniques, including AI and machine learning, to build sophisticated forecasting models and optimize resource allocation across a 3-year planning horizon. The ideal candidate combines expertise in workforce management principles, call center operations, and advanced analytics (SQL/Python) with the ability to translate complex data into actionable business strategies.
Job Responsibility:
Develop and maintain sophisticated capacity and demand forecasting models using historical data, market trends, and AI/ML techniques
Create statistical models for predictive forecasting with 3-year planning horizons
Conduct scenario planning and sensitivity analyses to evaluate business strategy impacts (product launches, seasonal changes, expansion)
Analyze large datasets using SQL and Python to monitor KPIs, utilization rates, and identify capacity bottlenecks
Build automated data pipelines and enhance planning tools for improved accuracy and efficiency
Utilize prompt engineering with Generative AI to automate report writing and optimize query performance
Optimize queries and automate report generation using AI-powered tools
Apply WFM principles to forecast labor demand/supply and optimize scheduling
Manage staff allocation to meet service levels while controlling costs and preventing burnout
Monitor staffing metrics including shrinkage, occupancy, and scheduling effectiveness
Partner with HR, Finance, Operations, Sales, and Data Science teams on capacity decisions
Transform complex datasets into compelling narratives for senior management
Present data-driven insights and strategic recommendations to executive stakeholders
Identify and mitigate risks related to capacity shortages or excesses
Requirements:
3-7 years of experience in capacity planning, workforce analytics, or similar analytical roles
Knowledge of WFM tools (e.g., Genesys, Verint, Assembled or specialized AI scheduling assistants)
Familiarity with forecasting, staffing metrics (shrinkage, occupancy), and scheduling strategies
Advanced proficiency in SQL for data extraction, manipulation, and analysis of large datasets
Experience in Python for data analysis, statistical modeling, and automation scripting