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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientists - **Company:** Airbnb - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $179,000.0 - $210,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Databases, Data Visualization, Python (Programming Language), SQL Databases, Large Language Models, Machine Learning Operations - **Published:** August 15, 2026 - **Apply:** https://careers.airbnb.com/positions/8123037?gh_jid=8123037 ## About the Role * 5+ years of industry experience in a quantitative analysis role with a Master's degree in a quantitative field (math / economics / statistics, and etc.), or 3+ years of experience with a Phd degree. * Strong knowledge of causal inference, experimentation, applied statistical modeling, and end-to-end ML development. * Skilled in statistical programming (Python or R) and database usage (SQL) * Demonstrated track record of owning a business or technical domain end-to-end at a prior company: setting your own roadmap, being the accountable expert others escalate to, and driving a problem to resolution. * Proven ability to communicate clearly and effectively to audiences of varying technical levels * Ability to work independently, set your own roadmap, and drive cross-functional alignment * Payments Fraud/Risk Domain expertise is a strong plus. * Familiarity with evaluating agentic or LLM-based systems (e.g., decision-quality measurement, human-in-the-loop calibration) is a plus. ## Description We are looking for a passionate data scientist to lead quantitative measurement efforts and bring novel scientific approaches to drive decision making across our platform's payment experience. This data scientist will perform careful hypothesis generation, causal inference framework development, and model development/evaluation to ideate and drive payment strategies on our platform. This role will have a particular focus on payments fraud mitigation and loss optimization, with the goal of making our platform safer for our community. Our Data Scientists have a deep understanding of causal framework development, statistical analysis, machine learning model development and evaluation strategies, and the complications of running experiment/quasi-experimental methods in a two-sided marketplace. They have keen business sense and are able to develop novel solutions to fraud and risk problems that don't have an established playbook and utilize their findings to communicate across a wide range of partners to drive our data & product roadmaps. They are not only the trusted data expert on their team, but also a storyteller. Examples of projects you may work on include, development of novel metrics and frameworks that can efficiently measure outcomes (often balancing competing tradeoffs), generating deep root cause investigations and long term impact measurements, and building/evaluating ML and agentic models to optimize guest, host, and business outcomes. A Typical Day: * Inference: Develop and apply causal inference methods, including experimental, econometric regressions, and quasi-experimental methods to measure a wide-range of platform/product impacts. * AI/ML: Build methods for robust evaluation of ML/AI model efficiency and performance. Ability to identify use-cases for and develop predictive models to classify, segment, and interpret our users' behavior. Support evaluation and optimization of agentic and LLM-based systems. * Optimization: Develop methodologies to explore/simulate the impact of new interventions and develop data products to optimize product/operational strategies. * Communication: Deliver robust research reports and effective data visualizations. Collaborate with and present to stakeholders to identify opportunities and communicate findings, and drive impact. * Empowerment: Think strategically about opportunities to improve and scale our brand measurement and customer insights. ## Related Videos - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Web-based Information Visualization](https://www.wearedevelopers.com/videos/84-web-based-information-visualization) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1520-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [TiDB, One Layer at a Time: How Distributed SQL Became an Agentic AI Backbone](https://www.wearedevelopers.com/videos/100117-tidb-one-layer-at-a-time-how-distributed-sql-became-an-agentic-ai-backbone) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)