Opendoor seeks an Applied Scientist skilled in machine learning to tackle complex quantitative challenges. Join our mission to innovate homeownership with data-driven strategies in a agile, collaborative workplace. In this role, you’ll address critical issues in marketing investment, customer acquisition, and conversion via advanced modeling techniques.

We require someone adept at applying machine learning, causal inference, and optimization to influence growth in a competitive landscape. Utilizing your Python expertise, you'll design models that directly impact decision-making processes across various departments. Key Responsibilities:
Build predictive models for seller intent and conversion
Develop customer lifetime value and marketing mix models




Optimize budget allocation for marketing spend
Apply causal inference to analyze marketing impacts
Collaborate with teams to implement models in practice

Requirements:
Robust Python programming for ML systems
Experience with predictive model deployment and evaluation
Background in causal inference and experimental design
Advanced degree in a quantitative field preferred
Capacity to handle imperfect data and ambiguous questions

Drive impactful decision-making with your modeling expertise at Opendoor.

📌 Applied Scientist In Machine Learning Vancouver (Canada)
🏢 Open Door
📍 Canada