Applied Scientist

About Opendoor

At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth stability and community. It's how families put down roots how neighborhoods strengthen how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We’ve built an end-to-end online experience that has already helped thousands of people and we’re just getting started.

We’re looking for an Applied Scientist  to work on some of the hardest quantitative problems at Opendoor. This role will focus primarily on structural modeling econometrics optimization and decision-making under uncertainty with applications spanning pricing resale strategy demand modeling and risk management.

This role will contribute to our broader valuation and pricing ecosystem and we’re looking for someone who can combine strong modeling intuition with hands-on execution and strong engineering to build practical solutions for a low-margin high-stakes business where small improvements can have an outsized impact.

You’ll work on problems like modeling post-listing demand estimating price elasticity designing experiments building structural models and developing optimizers that help us make better decisions across our products and inventory.

We’re a small nimble team so there’s ample opportunity to shape both the modeling direction and how these systems get used in production decision-making.

• 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

• 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

The base pay range for this position is $156800-$335000 annually plus RSUs. Pay within this range varies by work location and may also depend on your qualifications job-related knowledge skills and experience. We also offer a comprehensive package of benefits including unlimited PTO medical/dental/vision insurance life insurance and 401(k) to eligible employees.

#LI-RO

What We Do

Founded in 2014 Opendoor’s mission is to empower everyone with the freedom to move. We believe the traditional real estate process is broken and confusing. It often comes with unexpected costs the added burden of coordinating multiple third parties and the uncertainty of a transaction falling through. Our goal is simple: build a digital end-to-end customer experience that makes buying and selling a home simple certain and fast. We have assembled a dedicated team with diverse backgrounds and talents across engineering operations design operations mortgage finance legal and more to deliver strong results. More than 85000 customers have selected us as a trusted partner in handling one of their largest financial transactions.

Why Work With Us

We’re on a mission to power life’s progress one move at a time

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