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About the Role
We’re looking for an Applied Scientist to work on challenging quantitative problems at Opendoor, focusing on structural modeling, econometrics, optimization, and decision-making under uncertainty. This role will contribute to our valuation and pricing ecosystem, requiring strong modeling intuition, hands-on execution, and engineering skills to build practical solutions for a high-stakes business where small improvements can have a significant impact. You’ll work on problems like modeling post-listing demand, estimating price elasticity, designing experiments, building structural models, and developing optimizers. As part of a small, nimble team, you’ll have opportunities to shape modeling direction and production system usage.
Responsibilities
- Build models that help Opendoor make better decisions around pricing, resale strategy, and portfolio risk
- Develop demand and conversion models using both pre-listing and post-listing signals
- Design and improve optimization frameworks that balance objectives like margin, conversion, and risk
- Apply statistical, econometric, and mathematical modeling techniques to problems where structure matters and pure black-box prediction is not enough
- Design experiments and measurement approaches to quantify price elasticity, customer response, and product trade-offs
- Partner with Engineering, Product, and Operations to turn models into systems that influence real decisions
- Bring a pragmatic, hands-on approach: move quickly from idea to prototype to production-ready scientific component
Requirements
- Experience developing quantitative models to support real-world decision-making under uncertainty
- Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
- Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
- Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
- Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
- Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
Skills
- Python
- causal inference
- Bayesian modeling
- structural modeling
- demand forecasting
- pricing science
- mathematical optimization
- distributed data processing tools such as Pyspark
- machine learning methods
- deep learning
- large language models (LLMs)
- vision-language models (VLMs)
Education Level
- MS or PhD preferred
About the Company
- Opendoor is a low-margin, high-stakes business where small improvements can have an outsized impact.