- Job Type: Full-Time
- Function: Data Science
- Industry: Proptech
- Post Date: 04/28/2026
- Website: opendoor.com
- Company Address: 410 N Scottsdale Rd, Ste 1600, Tempe, Arizona 85281, US
About Opendoor
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 our goal is simple: build a digital, end-to-end customer experience that makes buying and selling a home simple, certain and fast.Job Description
About the Role
We’re looking for an experienced Applied Scientist to push the boundaries of applied machine learning and AI at Opendoor. While this role will have a significant impact on our valuation systems — ensuring we provide the most accurate and transparent pricing possible — the scope goes well beyond pricing. You’ll work across a range of challenging ML problems, from multi-modal modeling to operational optimization, helping us rethink how we use structured and unstructured data to make better decisions for our customers.
What You'll Need
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Strong software engineering and coding skills in Python, with experience contributing to production codebases
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5+ years of experience developing and deploying ML models end-to-end — from research and prototyping to implementation in production systems
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Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar
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Advanced degree (MS or PhD) in computer science, statistics, mathematics, or a related quantitative field
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Solid foundation in statistics and experimental design
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Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
Nice to Have
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Familiarity with Pyspark and distributed data processing
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Background in search, recommendation systems, or personalization
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Experience working with large language models (LLMs) or vision-language models (VLMs)
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A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data
What You'll Do
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Design and deploy architectural improvements to our deep neural network (DNN)-based home valuation models
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Build interpretable ML models that can help us explain pricing decisions to customers
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Incorporate unstructured data — like images, videos, or text — into our forecasting and valuation pipelines using cutting-edge AI models (LLMs, VLMs, etc.)
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Collaborate with Engineering and Ops to enhance our human-in-the-loop pricing systems
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Improve the feature engineering and model training pipelines that power our production systems
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Rethink our risk and optimization models using real-world data and domain insight
We’re a small, nimble team — there’s ample opportunity to work across the entire research and modeling stack.
Compensation
The base pay range for this position is $176,800-243,100 annually, plus RSUs and bonuses. 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.