Build interval-level volume forecasts using historical data and time series methods
Run Erlang C staffing calculations to convert forecast volume and AHT into FTE
Build capacity plans and scenario models (low/expected/high) for monthly to annual horizons
Monitor forecast accuracy (MAPE, bias) and refine models where variance recurs
Reforecast intraday volume and AHT and recalculate interval staffing when actuals diverge
From the employer’s posting
Develop interval-level, top-down volume forecasts using historical data, seasonality, and time series methods
Run Erlang C (or equivalent) staffing calculations to translate forecasted volume and AHT into required FTE by interval, queue, and skill.
Build and maintain capacity plans and headcount recommendations for monthly, quarterly, and annual planning horizons, including scenario models (low/expected/high) for known volume events.
Monitor forecast accuracy (e.g., MAPE, forecast bias) and refine models where recurring variance is identified.
Reforecast intraday volume and AHT when actuals diverge from plan, and recalculate interval staffing requirements
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About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
We’re an award-winning global outsourcer providing contact center and back office services on behalf of our global clients. Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
Forecasting and Capacity Planning
Develop interval-level, top-down volume forecasts using historical data, seasonality, and time series methods (moving averages, exponential smoothing, regression), selecting the technique best suited to each queue’s demand pattern.
Incorporate external inputs into the forecast, including marketing campaigns, price changes, billing cycles, regulatory events, and multi-jurisdiction public holiday calendars.
Run Erlang C (or equivalent) staffing calculations to translate forecasted volume and AHT into required FTE by interval, queue, and skill.
Build and maintain capacity plans and headcount recommendations for monthly, quarterly, and annual planning horizons, including scenario models (low/expected/high) for known volume events.
Execute the monthly forecast lock process, validating assumptions with stakeholders before staffing plans are finalised.
Monitor forecast accuracy (e.g., MAPE, forecast bias) and refine models where recurring variance is identified.
Coordinate with the Workforce Scheduler to ensure capacity plans translate cleanly into schedulable staffing requirements, and with Real-Time Analysts to support intraday reforecasting when actuals diverge from plan.
Real-Time Monitoring and Support
As needed, support real-time management alongside the Real-Time Analysts to ensure coverage is maintained, particularly during peaks, outages, unplanned absence, or reduced analyst cover.
Reforecast intraday volume and AHT when actuals diverge from plan, and recalculate interval staffing requirements so that coverage decisions are based on the latest demand view.
As needed, assist the Real-Time Analysts with real-time monitoring in Genesys Cloud CX, tracking service level, queue backlogs, arrival patterns, agent states, and schedule adherence across all vendors, and flag coverage gaps early.
Recommend intraday actions such as overtime, VTO, break movements, or skill changes, and communicate coverage risks to vendor WFM teams and supervisors.
Genesys Cloud CX Forecasting
Forecast build: Generate and maintain short-term and long-term forecasts in Genesys Cloud Workforce Engagement Management, including historical data selection, outlier and event handling, and forecast modifications.
Planning structure: Work within the agreed business units, planning groups, and service goal templates so that each queue, channel, and vendor is forecast consistently.
Validation: Compare Genesys-generated forecasts with client-provided forecasts and statistical models, and document the chosen forecast and its assumptions.
Data integrity: Audit historical volume, AHT, and routing data in Genesys, and work with the Workforce Manager to correct data issues caused by queue or routing changes.
Reporting: Use Genesys analytics and data exports to report forecast accuracy, forecast-to-actual variance, and capacity gaps.
Multi-Vendor Alignment
Split enterprise capacity requirements across vendors in line with agreed volume allocation and each vendor’s capability, and track each vendor’s planned staffing against its share.
Ensure all vendors plan to the same forecast, AHT, shrinkage, and occupancy assumptions set in the WFM as a Service framework.
Flag where a vendor’s hiring, attrition, or training plan puts client targets at risk, and model options to rebalance volume or capacity.
Provide forecasting and capacity data for vendor performance reviews and client governance forums.
Collaboration and Reporting
Present forecast assumptions, capacity plans, and variance clearly to operations, vendor, and client stakeholders, including non-technical audiences.
Support the Workforce Manager with headcount recommendations, reforecasts, and scenario models for client reviews.
Practise and ensure compliance with all organisation and client policies and procedures.