Opendoor seeks an Applied Scientist to tackle complex quantitative problems in a hands-on, collaborative 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
- Strong 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)
🏢 Opendoor
📍 Toronto