Community Support Forecasting and Demand Planning Analyst

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 that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

The Community Support org handles tens of millions of interactions yearly, engaging with Airbnb customers by phone, messaging, chat, or social media channels. The group handles hundreds of issues across categories including Cancellations, Account Issues, Refunds, Payments, Reservations, Extenuating Circumstances, Booking & Listing issues, Safety & Claims. The organization is globally distributed with offices in San Francisco, Dublin, Montreal, Seattle, Singapore, Manila, Gurgaon and an extensive partner network serving all regions. 

The Difference You Will Make:

We are looking for a seasoned Forecasting and Demand Planning Analyst on our Community Support (CS) team. This individual is responsible for demand forecasting and long-term planning across multi-channel contact center operations for our Global Operations team. This role ensures the organization has the right resources, at the right time, with the right skills to meet service level objectives while optimizing cost and productivity.

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: 

Demand Forecasting & Statistical Modeling

• Own short-term, mid-term, and long-term demand forecasting across all Global Operations teams and channels (phone, messaging, email, back-office etc.).
• 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.).
• Perform trend, seasonality, and variance decomposition; detect structural breaks, outliers, and demand anomalies.
• Quantify forecast uncertainty through confidence intervals, error distributions, and bias analysis.
• Perform scenario modeling for peak demand periods, product launches, growth initiatives, and unplanned demand events.
• Continuously assess model performance using statistical accuracy metrics (MAPE, RMSE, MAE, bias etc).
• Establish model governance standards, including documentation, validation, back-testing, and post-mortem analysis.
• Research, prototype, and implement new forecasting and optimization techniques as business needs evolve.
• Perform scenario planning and sensitivity analysis to quantify trade-offs between service levels, cost, and utilization.

Advanced Analytics

• 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.
• Use SQL and Python to extract, transform, and analyze large-scale operational datasets to monitor forecast accuracy, capacity gaps, utilization, and operational risk.

Decision Support & Stakeholder Communication

• 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.
• Align cross-functional stakeholders (Delivery, Product, Finance, HR, and others) to embed planning outputs into execution and operational decision-making.
• 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.

Your Expertise:

• 10+ years of experience in demand forecasting, capacity planning, workforce analytics, or applied analytics.
• Bachelor’s degree in Mathematics, Statistics, Operations Research, Engineering, Economics, Data Science, or a related quantitative field.
• Strong foundation in probability, statistics, and optimization.
• 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).
• Strong understanding of contact center metrics (AHT, ASA, service level, shrinkage, occupancy); experience supporting large-scale, multi-site, or global contact center environments preferred.
• Advanced analytical skills with strong proficiency in Excel, Google Sheets, SQL, Python and data visualization tools such as Tableau.
• Experience with WFM tools (e.g., NICE, Verint, Aspect) or planning platforms (e.g., Anaplan) preferred.
• Strong business acumen with the ability to balance cost efficiency and customer experience outcomes.
• Excellent communication, executive presentation, and stakeholder influence skills; ability to explain complex analytical concepts to non-technical audiences.
• Comfortable operating in fast-paced, ambiguous, and highly dynamic environments.

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list  If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: [email protected]. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.  

Reasonable Accommodations: We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

A Note on Recruiting Scams: Scammers sometimes pose as Airbnb recruiters to get money or personal information from candidates. A few things that will always be true for Airbnb’s hiring process: our open roles are posted on Airbnb’s Career’s Page at careers.airbnb.com, and our recruiters correspond only from @airbnb.com or @ext.airbnb.com email addresses. Our recruiters will never ask for your Social Security number, bank account details, passport, or payment app information while you are interviewing.  We’ll also never ask you to pay a fee, send money, deposit or cash a check, or purchase work-related equipment (such as a company laptop) during the interview process. We encourage candidates to remain vigilant of these recruiting scams and not share sensitive information if you do not believe an individual is actually affiliated with Airbnb.