WFM Capacity & Analytics Planner

About the Role:

Gusto is looking for a senior, technically minded workforce management planner who can design and scale AI-powered forecasting and capacity planning systems. You will report into the Planning People Empower and play a leading role in shaping how AI is adopted across forecasting, scheduling, and intraday operations. This role is equal parts strategic design and hands-on execution: you'll build the frameworks, pipelines, and governance structures that elevate WFM from reactive to predictive.

Here’s what you’ll do day-to-day:

Use AI to identify demand shifts, seasonal patterns, and emerging workforce risks before they impact operations.

Connect AI-generated insights to operational decisions across staffing, scheduling, and capacity planning.

Develop and maintain capacity plans, providing recommendations on hiring, staffing, and efficiency improvements for our CX teams.

Participate in an on-call PagerDuty rotation to monitor and respond to real-time alerts — including system outages, service level breaches, and routing failures — ensuring rapid escalation and resolution during off-hours incidents.

Design scalable AI-enabled WFM workflows across forecasting, scheduling, and intraday functions.

Build and maintain AI-powered WFM data pipelines that integrate multiple data sources (volume, AHT, shrinkage) to enable predictive and near-real-time insights.

Continuously monitor and adjust forecasts using AI-driven models and traditional methods as demand evolves.

Design governance frameworks for AI-enabled WFM workflows, including monitoring, validation, and escalation processes.

Partner with Legal, Data, and Product to ensure AI implementations meet organizational standards and compliance requirements.

Lead cross-functional AI initiatives for WFM, influencing how teams across the organization use AI in planning and operations.

Facilitate stakeholder meetings on forecasting, capacity planning, and AI adoption progress as member and facilitator aligned to the Operational Rhythm Meeting structure.

Identify potential risks to workforce capacity and proactively devise contingency plans.

Collaborate with stakeholders to implement risk mitigation strategies.

Evaluate and recommend process enhancements to boost efficiency and capacity utilization.

Analyze data to identify gaps and opportunities within the CX organization.

Here’s what we're looking for:

AI fluency required: Demonstrated ability to adopt and operationalize AI tools in a WFM or contact center context; designing or implementing AI/ML-powered forecasting, automation, or analytics workflows. Gusto is an AI-forward company and active AI use is expected daily.

Strong analytical and data visualization skills; demonstrated experience building dashboards and interactive reporting tools to surface WFM insights for operations and leadership; demonstrated analytical skills in volume forecasting, employee workloads, and staffing optimization.

Excellent judgment, communication, and problem-solving skills — able to translate complex data into clear, actionable recommendations for stakeholders at all levels.

Familiarity with COPC, ICMI, and/or SWPP standards is a plus.

Bachelor's degree or equivalent experience

7+ years in a capacity planning and forecasting role

Demonstrated ability to lead cross-functional initiatives and influence planning and operations practices across teams

Experience building or managing data pipelines that integrate multiple WFM data sources (volume, AHT, shrinkage, scheduling)

Proficiency in data modeling, statistical analysis, and data visualization

Experience in a high-volume, fast-paced contact center environment

Experience with BPOs

Familiarity with AI governance concepts including model monitoring, validation, and responsible AI practices

The cash compensation range for this role is $105,000/yearly to $129,00/yearly in Denver and Las Vegas, and most remote locations, and $98,775/yearly to $121,000/yearly in Phoenix. Remote locations will vary based on our geographical pay approach. Final offer amounts are determined by multiple factors, including candidate location, experience and expertise, and may vary from the level and amounts listed above.