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Airbnb

Connects travelers with stays and local activities

Senior Forecasting and Demand Planning Analyst

Supply Chain ManagementConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • At least 10 years of experience in demand forecasting, capacity planning, workforce analytics, or applied analytics.
  • A bachelor's degree in Mathematics, Statistics, Operations Research, Engineering, Economics, Data Science, or a related quantitative field.
  • A strong foundation in probability, statistics, and optimization.
  • Hands-on experience building and validating forecasting models, including time series analysis, exponential smoothing, ARIMA, regression, and hypothesis testing, as well as capacity models such as Erlang, queueing theory, and service-level and utilization modeling.
  • Strong understanding of contact center metrics, including average handle time, average speed of answer, service level, shrinkage, and occupancy.
  • Advanced analytical skills and strong proficiency in Excel, Google Sheets, SQL, Python, and data visualization tools such as Tableau.
  • Strong business acumen to balance cost efficiency and customer experience outcomes.
  • Ability to explain complex analytical concepts to non-technical audiences and communicate recommendations to stakeholders.
  • Ability to operate in fast-paced, ambiguous, and highly dynamic environments.
  • Must live in a state where Airbnb, Inc. has a registered entity.

Responsibilities

  • Own short-term, mid-term, and long-term demand forecasting across Global Operations teams and channels, including phone, messaging, email, and back-office channels.
  • Design, develop, and maintain statistically robust demand forecasting models using time series and machine learning techniques, including exponential smoothing, ARIMA, and regression-based models.
  • Perform trend, seasonality, and variance decomposition; detect structural breaks, outliers, and demand anomalies.
  • Quantify forecast uncertainty using confidence intervals, error distributions, and bias analysis.
  • Perform scenario modeling for peak demand periods, product launches, growth initiatives, and unplanned demand events.
  • Assess model performance using statistical accuracy metrics such as MAPE, RMSE, MAE, and bias.
  • Establish model governance standards, including documentation, validation, back-testing, and post-mortem analysis.
  • Research, prototype, and implement forecasting and optimization techniques as business needs evolve.
  • Perform scenario planning and sensitivity analysis to quantify trade-offs among service levels, cost, and utilization.
  • Partner with Analytics and Data Engineering to design and build scalable planning data pipelines and dashboards, and automate forecasting and capacity models to improve scalability, repeatability, and timeliness.
  • Use SQL and Python to extract, transform, and analyze large-scale operational datasets to monitor forecast accuracy, capacity gaps, utilization, and operational risk.
  • Present forecast assumptions, methodologies, risks, trade-offs, and recommendations in executive-ready formats; advise senior leadership and participate in cross-functional demand and capacity planning discussions.
  • Align cross-functional stakeholders, including Delivery, Product, Finance, and HR, to embed planning outputs into execution and operational decision-making.
  • Identify and implement process improvements, automation, and best practices in demand and capacity planning to optimize cost while maintaining or improving customer experience and service-level outcomes.

Desired Qualifications

  • Experience supporting large-scale, multi-site, or global contact center environments.
  • Experience with workforce management tools such as NICE, Verint, or Aspect, or planning platforms such as Anaplan.

About the Company

Airbnb

Connects travelers with stays and local activities

Airbnb runs an online marketplace where travelers book places to stay, local activities and personal services from hosts. Listings range from rooms in shared homes to entire properties and independent hotels, giving guests alternatives to conventional hotel stays. Hosts set prices and availability, while guests search by destination, compare listings and book through the website or mobile app. The platform handles payments and messaging, and earns service fees on reservations rather than renting out properties it owns; hosts receive payouts for the stays, experiences or services they arrange. Airbnb was founded in 2007 and has its headquarters in San Francisco, California.

Company size
5,001-10,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2007

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