The opportunity
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences…
What you'll do
Break down frontline performance by specialist, queue, vendor and site: analysing operational data to get to the level of detail the question actually needs.
Root-cause specialist-driven moves in SLA, AHT, accuracy and utilisation, and: deliver one accountable answer rather than a set of possibilities. For example: tracing an ATOQ SLA drop to a specific staffing change on a specific site, with the size of the effect quantified.
Monitor specialist-level metrics for problems that never show up in the: top-line numbers, and take a recommendation — not just a finding — to Frontline Delivery leadership.
Write the requirements for specialist metrics and dashboards, and refine them: with Tools Support, so the reporting frontline managers use every day answers their real questions.
Work the boundaries deliberately: hand causes that aren't specialist-driven to Business Intelligence, take Capacity Planning's approved volume forecasts as an input, and use Quality Analytics' case audits as evidence.
Sit in weekly business reviews and operational escalations, explaining what: the data means to people who need to make a decision in the next ten minutes.
What they're looking for
- Use AI tooling as a first resort rather than a last one, including our: internal AI data analytics tools, to get to an answer in minutes instead of hours.
- + years in operations analytics, workforce analytics, business intelligence: or a comparable analytical role, in an environment where operational decisions were made on your numbers.
- You write your own SQL to a high standard: complex joins, window functions, and the judgement to know when a result is wrong. You will not be building dashboards; you'll be specifying them.
- Deep contact-centre or high-volume operations knowledge: you understand SLA, AHT, occupancy, shrinkage, adherence and how a staffing decision on one site shows up in a queue metric two weeks later.
