Staff Data Scientist, Forecasting-Finance

Airbnb

11h•Remote

About The Position

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: Airbnb has become a global platform that connects travelers and hosts from over 34,000 cities. As such, it has collected a diverse set of numerical, textual, visual, and unstructured data, which can be mined for insights that will propel our community and product forward. We are looking for a talented Staff Data Scientist to join our Forecasting team, focusing on Revenue & Cancellation modeling. The Difference You Will Make: We are seeking a Staff Data Scientist to join our forecasting team, operating at the intersection of statistical forecasting and financial strategy. The role focuses on owning forecasting within the revenue pipeline and hierarchy, including model selection, system design, automation, and ongoing performance management. We are looking for a self-directed practitioner who can reason about evolving business dynamics, make principled tradeoffs, and ensure forecasts remain reliable and decision relevant as the business changes. This role is ideal for candidates with strong technical judgment who want to own how forecasts are built, operated, and used at the financial core of the business. The position emphasizes end-to-end forecasting systems, from data and models through automation, monitoring, and decision support, rather than isolated modeling work. If you are motivated by making forecasts reliable, interpretable, and consequential for real financial decisions, we encourage you to apply.

Requirements

9+ years of industry experience in a fast-paced tech environment with a BS/Master’s in a technical field related to mathematics, statistics, machine learning, or 3+ years of relevant experience and a PhD in similar fields.
Extensive industry experience applying forecasting in production settings, with demonstrated ownership of forecasting pipelines or decision systems, not just standalone models.
Expertise in SQL and relational databases, along with strong fluency in programming languages such as R, Python, and Stan.
Experience building automated modeling workflows, including backtesting frameworks, model validation, scheduled retraining, and performance monitoring.
Familiarity with version control, reproducibility, and data quality practices required for operating models in regulated or high visibility financial contexts.
Comfort working across disciplines and making tradeoffs between statistical rigor, engineering complexity, and business constraints.

Responsibilities

Own the design, operation, and evolution of end to end forecasting systems for revenue drivers, including data pipelines, model components, validation logic, and automated delivery into planning and financial workflows.
Select, adapt, and maintain forecasting approaches appropriate to each problem context, balancing accuracy, stability, interpretability, and operational cost rather than optimizing for modeling sophistication alone.
Engage in stakeholder management, effectively communicating with various teams and levels within the organization to gather input and share insights.
Drive the process of extracting actionable insights from complex data sets to influence business growth and strategic decision-making.
Continuously improve forecasting infrastructure and processes to reduce manual intervention, shorten cycle time, and increase trust in outputs.