Workforce Management Analyst
Merck Life Science
Description du poste
About the role
A detail-oriented and analytical Workforce Management (WFM) Analyst is sought to join the team in Costa Rica. The role covers forecasting, scheduling and real-time management of workforce resources to ensure optimal service levels, productivity and operational efficiency, working closely with operations and business leaders to balance staffing needs with business demand.
Key responsibilities
- Develop accurate short- and long-term volume forecasts based on historical data, trends and business inputs.
- Create and optimize staffing schedules to meet service level agreements (SLAs) and operational targets.
- Monitor real-time performance, adherence and service levels, adjusting staffing plans for intraday fluctuations.
- Analyze workforce data (attendance, shrinkage, occupancy, utilization) and produce regular reports and dashboards for stakeholders.
- Identify trends, risks and improvement opportunities in staffing efficiency and recommend corrective actions.
- Manage leave, overtime and schedule change requests in line with workforce planning requirements.
- Collaborate with operations managers and supervisors to align staffing plans with business priorities.
- Support capacity planning for new initiatives, seasonal peaks or organizational changes.
- Maintain and continuously improve WFM tools, processes and documentation.
Required profile
- At least 2 years of experience in data analytics, scheduling and forecasting, ideally in a shared services, contact center or operations environment.
- Strong analytical skills and excellent organizational skills, able to manage multiple priorities under tight deadlines.
- Strong written and verbal English (B2 minimum, C1 desired).
- Ability to work with cross-functional and global stakeholders.
Required skills
- Proficiency in Microsoft Excel; reporting/BI tools are a plus.
- Preferred: hands-on experience with Genesys workforce management or contact center platforms, and familiarity with other WFM tools such as NICE, Verint or Aspect.
- Familiarity with statistical forecasting methods and WFM best practices is preferred.
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Merck Life Science