[Remote] Community Support Forecasting and Demand Planning Analyst
Note: The job is a remote job and is open to candidates in USA. Airbnb is a global company that connects hosts and guests for unique stays and experiences. They are seeking a seasoned Forecasting and Demand Planning Analyst to manage demand forecasting and long-term planning for their Community Support team, ensuring the right resources are in place to meet service level objectives while optimizing costs and productivity.
Responsibilities
ā¢ Own short-term, mid-term, and long-term demand forecasting across all Global Operations teams and channels (phone, messaging, email, back-office etc.)
ā¢ Design, develop, and maintain statistically robust demand forecasting models using time series and machine learning techniques (e.g., exponential smoothing, ARIMA, regression-based models etc.)
ā¢ Perform trend, seasonality, and variance decomposition; detect structural breaks, outliers, and demand anomalies
ā¢ Quantify forecast uncertainty through confidence intervals, error distributions, and bias analysis
ā¢ Perform scenario modeling for peak demand periods, product launches, growth initiatives, and unplanned demand events
ā¢ Continuously assess model performance using statistical accuracy metrics (MAPE, RMSE, MAE, bias etc)
ā¢ Establish model governance standards, including documentation, validation, back-testing, and post-mortem analysis
ā¢ Research, prototype, and implement new forecasting and optimization techniques as business needs evolve
ā¢ Perform scenario planning and sensitivity analysis to quantify trade-offs between service levels, cost, and utilization
ā¢ In partnership with the Analytics and Data Engineering team, design and build scalable planning data pipelines, dashboards, and automate forecasting and capacity models to improve scalability, repeatability, and timeliness
ā¢ Use SQL and Python to extract, transform, and analyze large-scale operational datasets to monitor forecast accuracy, capacity gaps, utilization, and operational risk
ā¢ Present forecast assumptions, methodologies, risks, trade-offs, and recommendations in clear, executive-ready formats and act as a trusted advisor to senior leadership and participate in demand/capacity planning discussions in cross-functional forums
ā¢ Align cross-functional stakeholders (Delivery, Product, Finance, HR, and others) to embed planning outputs into execution and operational decision-making
ā¢ Identify and implement process improvements, automation, and best practices in the demand and capacity planning area to optimize cost while maintaining or improving customer experience and service-level outcomes
Skills
ā¢ 10+ years of experience in demand forecasting, capacity planning, workforce analytics, or applied analytics
ā¢ Bachelor's degree in Mathematics, Statistics, Operations Research, Engineering, Economics, Data Science, or a related quantitative field
ā¢ Strong foundation in probability, statistics, and optimization
ā¢ Hands-on experience building and validating forecasting models (time series analysis, exponential smoothing, ARIMA, regression, hypothesis testing) and capacity models (Erlang, queueing theory, service-level and utilization modeling)
ā¢ Strong understanding of contact center metrics (AHT, ASA, service level, shrinkage, occupancy); experience supporting large-scale, multi-site, or global contact center environments preferred
ā¢ Advanced analytical skills with strong proficiency in Excel, Google Sheets, SQL, Python and data visualization tools such as Tableau
ā¢ Strong business acumen with the ability to balance cost efficiency and customer experience outcomes
ā¢ Excellent communication, executive presentation, and stakeholder influence skills; ability to explain complex analytical concepts to non-technical audiences
ā¢ Comfortable operating in fast-paced, ambiguous, and highly dynamic environments
ā¢ Strong understanding of contact center metrics (AHT, ASA, service level, shrinkage, occupancy); experience supporting large-scale, multi-site, or global contact center environments preferred
ā¢ Experience with WFM tools (e.g., NICE, Verint, Aspect) or planning platforms (e.g., Anaplan) preferred
Benefits
ā¢ Bonus
ā¢ Equity
ā¢ Benefits
ā¢ Employee Travel Credits
Company Overview
ā¢ Airbnb is an online community marketplace for people to list, discover, and book accommodations through mobile phones or the Internet. It was founded in 2008, and is headquartered in San Francisco, California, USA, with a workforce of 5001-10000 employees. Its website is https://www.airbnb.com.
Company H1B Sponsorship
ā¢ Airbnb has a track record of offering H1B sponsorships, with 27 in 2026, 234 in 2025, 176 in 2024, 160 in 2023, 270 in 2022, 250 in 2021, 274 in 2020. Please note that this does not guarantee sponsorship for this specific role.
Responsibilities
ā¢ Own short-term, mid-term, and long-term demand forecasting across all Global Operations teams and channels (phone, messaging, email, back-office etc.)
ā¢ Design, develop, and maintain statistically robust demand forecasting models using time series and machine learning techniques (e.g., exponential smoothing, ARIMA, regression-based models etc.)
ā¢ Perform trend, seasonality, and variance decomposition; detect structural breaks, outliers, and demand anomalies
ā¢ Quantify forecast uncertainty through confidence intervals, error distributions, and bias analysis
ā¢ Perform scenario modeling for peak demand periods, product launches, growth initiatives, and unplanned demand events
ā¢ Continuously assess model performance using statistical accuracy metrics (MAPE, RMSE, MAE, bias etc)
ā¢ Establish model governance standards, including documentation, validation, back-testing, and post-mortem analysis
ā¢ Research, prototype, and implement new forecasting and optimization techniques as business needs evolve
ā¢ Perform scenario planning and sensitivity analysis to quantify trade-offs between service levels, cost, and utilization
ā¢ In partnership with the Analytics and Data Engineering team, design and build scalable planning data pipelines, dashboards, and automate forecasting and capacity models to improve scalability, repeatability, and timeliness
ā¢ Use SQL and Python to extract, transform, and analyze large-scale operational datasets to monitor forecast accuracy, capacity gaps, utilization, and operational risk
ā¢ Present forecast assumptions, methodologies, risks, trade-offs, and recommendations in clear, executive-ready formats and act as a trusted advisor to senior leadership and participate in demand/capacity planning discussions in cross-functional forums
ā¢ Align cross-functional stakeholders (Delivery, Product, Finance, HR, and others) to embed planning outputs into execution and operational decision-making
ā¢ Identify and implement process improvements, automation, and best practices in the demand and capacity planning area to optimize cost while maintaining or improving customer experience and service-level outcomes
Skills
ā¢ 10+ years of experience in demand forecasting, capacity planning, workforce analytics, or applied analytics
ā¢ Bachelor's degree in Mathematics, Statistics, Operations Research, Engineering, Economics, Data Science, or a related quantitative field
ā¢ Strong foundation in probability, statistics, and optimization
ā¢ Hands-on experience building and validating forecasting models (time series analysis, exponential smoothing, ARIMA, regression, hypothesis testing) and capacity models (Erlang, queueing theory, service-level and utilization modeling)
ā¢ Strong understanding of contact center metrics (AHT, ASA, service level, shrinkage, occupancy); experience supporting large-scale, multi-site, or global contact center environments preferred
ā¢ Advanced analytical skills with strong proficiency in Excel, Google Sheets, SQL, Python and data visualization tools such as Tableau
ā¢ Strong business acumen with the ability to balance cost efficiency and customer experience outcomes
ā¢ Excellent communication, executive presentation, and stakeholder influence skills; ability to explain complex analytical concepts to non-technical audiences
ā¢ Comfortable operating in fast-paced, ambiguous, and highly dynamic environments
ā¢ Strong understanding of contact center metrics (AHT, ASA, service level, shrinkage, occupancy); experience supporting large-scale, multi-site, or global contact center environments preferred
ā¢ Experience with WFM tools (e.g., NICE, Verint, Aspect) or planning platforms (e.g., Anaplan) preferred
Benefits
ā¢ Bonus
ā¢ Equity
ā¢ Benefits
ā¢ Employee Travel Credits
Company Overview
ā¢ Airbnb is an online community marketplace for people to list, discover, and book accommodations through mobile phones or the Internet. It was founded in 2008, and is headquartered in San Francisco, California, USA, with a workforce of 5001-10000 employees. Its website is https://www.airbnb.com.
Company H1B Sponsorship
ā¢ Airbnb has a track record of offering H1B sponsorships, with 27 in 2026, 234 in 2025, 176 in 2024, 160 in 2023, 270 in 2022, 250 in 2021, 274 in 2020. Please note that this does not guarantee sponsorship for this specific role.