Opendoor seeks an Applied Scientist to tackle complex quantitative problems in a hands-on, team-oriented environment. Focus on econometrics, pricing optimization, and decision-making under uncertainty. In this role, you will contribute significantly to Opendoor's valuation and pricing ecosystem, requiring robust modeling intuition and practical execution.

You will engage in developing quantitative models for real-world decision-making and optimize solutions for a competitive marketplace. The position emphasizes the importance of small, impactful improvements within a low-margin business model. Key Responsibilities:
Build models for pricing, resale strategy, and portfolio risk
Develop demand models using pre- and post-listing signals




Design optimization frameworks balancing margin and risk
Apply econometric techniques where structure is essential
Partner with teams to integrate models into decision systems Requirements:
Experience in quantitative modeling under uncertainty
Solid Python coding skills for production-quality solutions
Background in causal inference or demand forecasting
Advanced degree in a quantitative field preferred
Strong communication skills with cross-functional teams Develop your expertise in applied science while navigating complex modeling challenges at Opendoor.

📌 Applied Scientist Role At Opendoor Toronto (Canada)
🏢 Opendoor
📍 Canada