WFM Senior Capacity Planning Analyst

About the role

As WFM Senior Capacity Planning Analyst, you will act as the strategic owner of the workforce supply-and-demand ecosystem. You will move beyond traditional spreadsheets to build a predictive, financially aligned and highly optimized capacity function.

Key responsibilities

• Own the end-to-end capacity planning process, set standards for planning horizons, documentation and methodology, and review and approve plans built by Planning Analysts.
• Apply statistical techniques and use Python, R and SQL to build forecasting models and define risk bands under uncertainty.
• Act as the primary WFM owner for inputs into the financial rolling forecast, working with Finance to align staffing models with corporate financial targets and cost objectives.
• Lead demand validation discussions with senior Operations, Analytics and Demand Management leaders, challenging assumptions with data to secure formal plan sign-offs.
• Design "what-if" scenarios covering demand volatility, hiring delays and productivity shocks, giving executives clear options and trade-offs.
• Oversee the translation of capacity plans into hiring strategies with Talent Acquisition, handover to Scheduling, and collaboration with Analytics on automated data pipelines.
• Mentor Planning Analysts and develop their analytical rigor, financial thinking and stakeholder management.

Required profile

• 4-7 years of experience in Workforce Management, Capacity Planning, Forecasting, Data Science or Operations Analytics.
• Proven track record of owning planning cycles, managing financial alignment and driving stakeholder sign-offs in complex, high-volume, multi-skill environments.
• Ability to challenge assumptions with evidence, lead difficult trade-off conversations and influence senior stakeholders without direct authority.
• Strong ownership mindset: structured, analytical, forward-looking and calm under pressure.

Required skills

• Predictive or statistical analysis with Python, R or equivalent environments (time-series or regression-based modeling).
• Advanced SQL, including complex queries, data modeling and joining multiple operational datasets.
• Advanced spreadsheet skills and a bias toward automation.