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. Backed by NEA, Norwest and SoftBank VF.
About the role
We’re looking for an Applied Scientist to work on some of the hardest quantitative problems at Opendoor. This role will focus primarily on machine learning, causal inference, optimization, and decision-making under uncertainty, with applications spanning marketing investment, customer acquisition, lifecycle engagement, and conversion. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Strong Python skills, with experience building maintainable software and contributing to production ML systems
- Experience taking predictive models from problem definition and training through deployment, evaluation, and iteration, with a strong foundation in classification and statistical modeling
- Applied experience in causal inference and experimental design, including estimating incremental effects and reasoning about confounding, selection bias, and uncertainty
- Ability to evaluate models using both predictive performance and the business outcomes of the decisions they inform
- Comfort working with imperfect data, delayed outcomes, and ambiguous business questions, and translating findings into clear recommendations for technical and business partners
- An advanced degree (MS or PhD preferred) in statistics, economics, computer science, mathematics, operations research, or a related quantitative field, or equivalent applied research experience
More about this role
About the Role
We’re looking for an Applied Scientist to work on some of the hardest quantitative problems at Opendoor. This role will focus primarily on machine learning, causal inference, optimization, and decision-making under uncertainty, with applications spanning marketing investment, customer acquisition, lifecycle engagement, and conversion.
This role will contribute to our broader growth 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 in acquisition efficiency and customer conversion can have an outsized impact.
You’ll work on problems like predicting seller intent and conversion, estimating customer lifetime value, building marketing mix models, and developing optimizers that help us allocate spend and identify which customer interactions drive incremental growth.
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.
- Strong Python skills, with experience building maintainable software and...
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