Workforce Management Analyst

We are seeking an analytical and forward-thinking Workforce Analyst to support workforce planning for a Home Services contact center.

This role is responsible for developing accurate call volume forecasts, staffing models, and capacity plans that enable the organization to achieve customer experience, service level, and cost objectives.

The primary focus of this role is leveraging Artificial Intelligence (AI), predictive analytics, and advanced Microsoft Excel modeling to improve forecasting accuracy and uncover actionable business insights.

The successful candidate will use AI-powered tools and forecasting technologies to identify trends, detect anomalies, model demand drivers, evaluate scenarios, and generate data-driven staffing recommendations.

While workforce management experience is important, we are specifically seeking candidates who embrace AI as a strategic forecasting tool and understand how to combine AI-generated insights with operational expertise and human judgment.

This position is ideal for an intermediate-to-senior workforce professional who has experience using AI solutions, advanced analytics, and Excel-based forecasting techniques to solve complex workforce planning challenges in a high-volume contact center environment.

• Utilize AI-powered forecasting tools and predictive analytics platforms to improve call volume forecasting accuracy.
• Leverage machine learning and AI-generated insights to identify emerging trends, seasonality patterns, demand drivers, and operational risks.
• Evaluate AI-generated forecasts and apply business knowledge to validate assumptions and refine outputs.
• Use AI tools to automate data analysis, trend identification, anomaly detection, and forecast variance investigations.
• Integrate traditional forecasting methodologies with AI-driven recommendations to create accurate and actionable demand plans.
• Continuously assess new AI technologies and forecasting capabilities that can improve workforce planning effectiveness.

• Develop monthly, weekly, daily, and interval-level forecasts for inbound contact center demand.
• Analyze historical call volumes, AHT, service levels, customer behavior, marketing activity, weather impacts, and operational changes to support forecasting decisions.
• Translate forecasted workload into staffing requirements, productive hours, schedules, and FTE recommendations.
• Create multiple forecast scenarios to assess business impacts and staffing risks.
• Monitor forecast accuracy and identify opportunities to improve forecasting models and assumptions.

• Combine AI-generated insights with advanced Excel analysis to deliver workforce recommendations.
• Build dashboards, forecasting models, and reporting tools that support data-driven decision-making.
• Utilize large datasets to uncover trends, root causes, and performance improvement opportunities.
• Present findings and recommendations to Operations, Workforce Management, and senior leadership.

• 4–7+ years of Workforce Management, Forecasting, Capacity Planning, Workforce Analytics, or Contact Center Operations experience.
• Demonstrated experience using Artificial Intelligence, predictive analytics tools, machine learning platforms, or AI-assisted forecasting solutions to support business planning and forecasting decisions.
• Advanced Microsoft Excel expertise, including forecasting models, Power Query, Pivot Tables, statistical analysis, scenario modeling, and data visualization.
• Experience translating demand forecasts into staffing plans and workforce recommendations.
• Strong understanding of contact center metrics including call volume, AHT, service level, ASA, occupancy, shrinkage, and forecast accuracy.
• Proven ability to evaluate AI-generated recommendations and apply business judgment to improve forecast outcomes.

• Experience using generative AI tools (e.g., Microsoft Copilot, or similar platforms) to support forecasting analysis, reporting, trend identification, and productivity improvements.
• Advanced Microsoft Excel capability, including the ability to build and maintain complex forecasting and staffing models.
• Experience working with predictive analytics, machine learning models, or advanced forecasting software.
• Knowledge of Power BI, SQL, Python, R, or other analytical tools used in workforce planning environments.
• Experience implementing AI-driven process improvements or automation initiatives within Workforce Management functions.

• Machine learning forecasting concepts
• Predictive modeling
• AI-driven trend analysis
• Pattern recognition
• Forecast optimization
• Anomaly detection
• Scenario modeling
• Data interpretation and validation

• Statistical forecasting models
• Trend and seasonality analysis
• Forecast accuracy measurement
• Driver-based forecasting
• Workforce capacity calculations
• Power Query and data transformation
• Advanced formulas and automation

• Staffing requirement calculations
• Capacity planning
• Erlang concepts
• Shrinkage modeling
• Service level forecasting
• Intraday planning
• Forecast performance analysis

Enercare is an equal opportunity employer.

We are committed to equal employment opportunity regardless of race, colour, ancestry, national origin, religion, sex, age, sexual orientation, gender identity, citizenship, marital status, disability, pregnancy, military status, protected veteran status or other characteristics protected by applicable law.

Enercare’s recruitment process includes accommodation for applicants with disabilities in accordance with applicable provincial accessibility laws and regulations.

All accommodations will take into account the applicant’s accessibility needs due to disability and are available upon request.

Our company leverages artificial intelligence (AI) tools as part of the candidate screening process to help review applications efficiently and fairly.

These tools may assist in evaluating qualifications against job requirements.

All decisions regarding hiring are ultimately made by our recruitment team.

All roles posted are opportunities we’re actively recruiting for, unless stated otherwise.