Community Support Forecasting and Demand Planning Analyst - Airbnb, United States

Vacations Worldwide

Northern (KY)

Hybrid

USD 90,000 - 140,000

Full time

14 days+
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Job summary

Airbnb in the United States is seeking a Community Support Forecasting and Demand Planning Analyst to own demand forecasting across Global Operations channels (phone, messaging, email, back-office) and to design robust statistical models that support scalable workforce decisions.

The role blends planning, analytics and partner management in a fast-changing environment, with spike-prone travel support demand and a focus on data-driven insights to optimize staffing.

Qualifications

  • Demand forecasting and statistical modeling across Global Operations channels.
  • Designing and maintaining robust statistical models.

Responsibilities

  • Own short-, mid-, and long-term demand forecasting across all Global Operations channels.
  • Design, develop and maintain statistically robust models to support workforce decisions.

Skills

Statistical modeling
Contact centre experience
Forecasting analytics

Job description

  • Community Support Forecasting and Demand Planning Analyst - Airbnb, United States
Community Support Forecasting and Demand Planning Analyst - Airbnb, United States

Employer: Airbnb | Location: United States | Type: Full-time

The role combines planning, advanced analytics and business partnership to drive scalable, data-driven workforce decisions in a complex, fast-changing environment.

A typical day covers demand forecasting and statistical modeling: owning short-, mid- and long-term demand forecasting across all Global Operations teams and channels - phone, messaging, email and back-office - and designing, developing and maintaining statistically robust models.

Travel support demand is famously spiky, driven by weather, disruption and seasonality, which makes accurate forecasting one of the highest-value analytics jobs in the sector.

Good fit for: workforce planning analysts, demand planners and operations analysts with strong statistical modeling skills and contact-centre experience.

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