Community Support Analyst, Forecasting and Demand Planning

🕒 April 24

🇺🇸 United States – Remote

💵 $168k - $210k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🧐 Analyst

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Airbnb

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2007

👥 B2C

🛍️ eCommerce

💰 Post-IPO Equity on 2020-12

B2C • eCommerce • Hospitality

Airbnb is a global online marketplace that connects people looking for accommodation with hosts offering unique and diverse lodging options, often in residential properties. Users can book spaces ranging from one-bedroom apartments to entire homes and boutique hotels. Airbnb also offers experiences, allowing guests to book activities hosted by locals, providing an authentic travel experience.

📋 Description

• 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. • 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. • 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Bonus • Equity • Employee Travel Credits