Senior Workforce Management Analyst

Job Ref ID: JR0088866

You will lead how we forecast and staff our outsourced customer support hubs, so we have the right agents at the right time at the lowest possible cost. 

Over the next 12-18 months, you’ll make our forecasting more robust by moving from hub-by-hub to country-centric and global forecasting, and plan for AI-driven savings. You’ll use data to find where we overstaff or lose productivity, and drive the Productivity SteerCo that turns these findings into savings, working with hubs, Service Delivery and process owners who don’t report to you

• Strengthen and streamline the forecasting process: define best practices, including how and when we align with hubs and internal stakeholders. Separate the pure contact forecast from hours planning, and move from hub-by-hub to country-centric forecasting. Set up standardized checks, alarm tooling and internal benchmarking of forecast quality, so every forecast follows the same standard.

• Move toward a global forecast: together with our data scientist, aggregate and forecast volumes at a higher level, especially translated contact reasons in international hubs. Distribute the global needs to hubs based on their performance.

• Plan for AI agents and AI translation: forecast how AI agents change human contact volumes, including the share of contacts transferred to humans when the AI can’t fully solve them. Propose how to ramp volumes between hubs as AI translation rolls out (e.g., toward more cost-efficient hubs). You’ll work with the MX verticals and hub owners.

• Raise forecast accuracy and cut overstaffing: improve WAPE and bias through better models, alignment with our internal teams and higher-volume aggregations, and forecast a few hubs yourself to ground the improvements in practice. Quantify the cost of overstaffing and track the savings. You’ll work with the MX verticals, who provide the inputs (rollouts, experiments).

• Drive the Productivity SteerCo and generate savings: be the main source of input to the SteerCo. Identify productivity opportunities through data-driven deep dives, including benchmarking handling times (AHT) between hubs and against ~70 markets from other entities in the group. Keep an overview of all savings opportunities, prioritize them by monetary impact, and follow up with Service Delivery (process adherence), vertical owners (process descriptions) and Product until they are delivered as cost savings.

• 3+ years in a data analyst or analytics engineer role, with a track record of turning analysis into business decisions

• Data and influence. You form a hypothesis, test it with SQL, Python and statistics knowledge, and quantify the impact. You know that data alone doesn’t always convince: you identify who is affected by a decision, who can block it and who can help, and you build support early.

• Project delivery. You manage multi-step projects from scoping and prioritization to rollout, monitor the operations afterwards and correct course when needed. You don’t stop at the insight: you follow up until the result shows in the metrics.

• Creative problem-solving. You know and apply best practices, but you don’t stop at “how it’s always been done.” You question the accepted approach and come up with solutions nobody else has tried.

• AI fluency. AI is part of how you work. You’ve built repeatable workflows, know what to delegate and what to keep, and always verify the output.

• Experience with time series forecasting methods, backtesting frameworks, accuracy metrics (WAPE, BIAS), and familiarity with data science. 

• Experience in a platform or marketplace business serving several stakeholder groups, or in workforce management and agent planning.