We are looking for economists with backgrounds in causal inference and in forecasting. We have a range of positions, so we welcome candidates at all levels of experience, with preference towards more experienced candidates. We solve an array of challenging problems in both domains. In causal inference, we analyze short and long-term impacts of supply chain management (e.g. shipping speeds, late deliveries); lifts from merchandising actions in high-dimensional, noisy data (e.g. additional review or imagery); and long-term consequences of price perception, using both observational and experimental data. In forecasting, we have to provide monthly forecasts for millions of products, ideally incorporating facts about substitutability of our products. We partner directly with several business teams to understand each problem space deeply, identify appropriate and efficient statistical solutions, and embed the resulting models into business decision-making and/or algorithms.

Wayfair is a Fortune 500 technology company, selling home goods (including furniture), primarily online. As an economist, you will be joining us at an exciting moment in the company’s growth and help to solidify our internal economics culture. The existing group (~15 economists across Wayfair) provides a powerful community of colleagues, while still allowing you to have an outsized opportunity for impact at the company level and visibility to senior leaders across the organization. You will also work with non-economist data scientists and engineers, sharing a range of perspectives on how to best approach problems. In contrast to other established econ in tech roles, you will likely be the first economist working on a particular problem or within a business vertical, starting projects from scratch rather than iterating on a versioned release of a legacy model.

• Ph.D. in economics or another related field (quantitative marketing, political science, applied statistics, etc).
• Experience in industry, consulting, government, or academia is a plus.
• Strong intuition about either causal inference, applied econometrics, and applied microeconomics or forecasting, including a wide and deep applied econometric toolkit. Some experience with machine learning is a plus.
• Ability to effectively work with business leads and data scientists, including strong verbal and written communication skills, ability to synthesize conclusions for non-experts, and desire to influence business decisions.
• Genuine interest in collaborating and mentoring other scientists on the team and across Wayfair.
• Experience implementing models in Python is a plus.
• Prior experience working with large datasets, leveraging tools like Spark, Hive, Airflow and experience with Google Cloud Platform is a plus.