Applied Scientist in Machine Learning

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 dynamic, collaborative environment. 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:

• Strong 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. #J-18808-Ljbffr