Applied Scientist: Growth ML & Causal Inference

Opendoor; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

Opendoor is seeking an Applied Scientist to tackle challenging quantitative problems across marketing investment, customer acquisition, lifecycle engagement, and conversion. You will build predictive models, engage in causal inference, and develop optimization solutions to allocate spend and improve conversion in a low-margin, high-stakes business.

You will collaborate with Marketing, Product, Engineering, and Sales, delivering production-ready models and robust evaluation to inform strategic

Qualifications

• MS or PhD in statistics, economics, computer science, mathematics, operations research or related quantitative field, or equivalent applied research experience.
• Strong Python and production ML experience with classification and statistical modeling.
• Applied experience in causal inference and experimental design, including estimating incremental effects and handling uncertainty.

Responsibilities

• Build models and decision systems that support profitable growth through better customer acquisition and engagement.
• Develop intent, conversion, and lifetime value models to optimize acquisition and engagement.
• Build and improve marketing measurement and optimization systems that guide budgeting and spend across channels, markets, and time.
• Apply causal inference to experimental and observational data to estimate incremental marketing impact across customers and markets.
• Partner with Marketing, Product, Engineering, and Sales to turn models into production-ready systems that influence real decisions.
• Move quickly from research and prototyping to production, and own ongoing model evaluation and improvement.

Skills

Python

Production ML systems

Predictive modeling

Causal inference

Experimental design

Model evaluation

Data wrangling

Stakeholder communication

Education

MS/PhD in statistics or related field

Tools

PySpark

Job description

Opendoor is seeking an Applied Scientist to tackle challenging quantitative problems across marketing investment, customer acquisition, lifecycle engagement, and conversion. You will build predictive models, engage in causal inference, and develop optimization solutions to allocate spend and improve conversion in a low-margin, high-stakes business.

You will collaborate with Marketing, Product, Engineering, and Sales, delivering production-ready models and robust evaluation to inform strategic