Join Opendoor as an Applied Scientist and tackle challenging quantitative problems with a focus on machine learning and decision-making. This role is integral to optimizing customer acquisition and engagement.

As an Applied Scientist at Opendoor, you will be engaged in building models that drive profitable growth in the homeownership ecosystem. Your work will involve causal inference, optimization, and customer lifecycle analysis, fundamentally enhancing our marketing strategies. This role requires robust Python skills and the ability to translate complex findings into actionable insights.

Key Responsibilities:
• Build models to enhance customer acquisition and engagement
• Develop intent and conversion optimization models
• Improve marketing measurement systems and budget allocation




• Apply causal inference to validate marketing impact
• Collaborate with cross-functional teams to implement decision systems

Requirements:
• Proficient in Python with production ML experience
• Advanced degree in statistics, economics, or related field
• Strong knowledge in causal inference and experimental design
• Ability to work with imperfect data and ambiguous questions
• Experience in predictive modeling and production deployment

Bring your quantitative skills and problem-solving expertise to Opendoor, shaping the future of homeownership.
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📌 Machine Learning Applied Scientist at Opendoor (British Columbia)
🏢 Rippling
📍 British Columbia