Applied Scientist

Experience in pricing, marketplace modeling, revenue management, supply/demand systems, inventory optimization, or risk modeling

Background in real estate, housing, finance, or adjacent marketplace domains

Familiarity with distributed data processing tools such as Pyspark

Experience with machine learning methods broadly, including where deep learning can complement structured statistical modeling

Experience working with large language models (LLMs) or vision-language models (VLMs)

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