Staff Data Scientist, Open Exchange

Since Opendoor first started operating in 2014, we’ve learned a lot about buying, managing, and selling real estate. The Open Exchange business aims to share our learnings by offering our technology and processes to institutional single-family-home investment partners. Open Exchange is uniquely positioned to be the vertically integrated lead, data, and transaction solution – the industry source of truth with the most scalable transaction engine.

As a Staff Data Scientist in our Open Exchange Data team, you will primarily work on customer-facing data projects that are the fundamental underpinnings to our success. You will build predictions and recommendation models that enable our partners to buy more homes that fit their underwriting criteria. You will build market-leading data products for our institutional residential real estate partners that uniquely predict such things as rental prices, HOA dues, and comparables that we can monetize to drive fee-based revenue. If you are looking for a role that profoundly and immediately impacts the business, this is the role for you.

• Create customer-facing data science products such as rental price predictions, HOA predictions, housing comparables, and recommendations / lead scores
• Identify the appropriate data science models and data sets to include in machine learning models, as well as the data optimization steps and hyperparameter tuning needed to optimize model accuracy
• Partner with engineering and product to bring models from prototype to scalable production
• Measure the impact of your work on both our business and our customers
• Establish best practices for rigorous, trusted, reproducible data science work
• Become a domain expert in real estate
• Contribute individual analytics and modeling work, as well as coach and uplevel the technical bar of the team

• 7+ years of industry experience post academia, with an advanced degree in a quantitative field
• Able to build, productionalize and monitor machine learning / data science models with not only independence, but also an expertise level that guides our approach
• Expert level domain expertise in one of the following domains; pricing models, recommendation / lead score models, geospatial models, or operationalizing data science and machine learning on Databricks with MLflow
• Expertise with both Python and SQL
• Experience scheduling and operating data processing workflows
• Proficiency in working with complex and fast-evolving data sets

• Experience in real estate or financial services
• Experience with optimizing dynamic pricing or operations research
• Strong written and verbal communication skills to influence non-technical audiences with analytical insights and data visualizations

Remote roles in the US are available in all states EXCEPT Hawaii, Alaska, Montana, or any US Territories. 

The base salary range for this position in Colorado, Connecticut, Washington, and New Jersey is $192,000 - $291,500yr, and in California and New York City is $192,000 - $291,500yr. Base salary may vary depending on relevant experience, skills, geographic location, and business needs. We offer a comprehensive package of benefits including paid time off, 12 paid holidays per year, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.

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