Payments Data Scientist: Fraud & Causal Insights (Remote)

Airbnb; United States; On-site; USD 179,000 - 210,000; Full time

Job summary

Airbnb is seeking a data scientist to lead quantitative measurement for payments, focusing on fraud mitigation and loss optimization. You will develop causal inference frameworks, build ML models, and communicate insights to cross-functional partners to improve platform safety and efficiency.

The role requires deep statistical expertise, experience with end-to-end ML, and the ability to operate in a fast-paced, globally distributed environment. Remote eligibility within the US is available.

Qualifications

• 5+ years in a quantitative analysis role with a quantitative degree, or 3+ years with a PhD.
• Strong knowledge of causal inference, experimentation, and end-to-end ML development.
• Proficiency in statistical programming (Python or R) and database usage (SQL).
• Proven ability to own a domain end-to-end and drive a problem to resolution.
• Ability to communicate clearly to non-technical audiences.

Responsibilities

• Develop and apply causal inference methods to measure a wide range of platform impacts.
• Build and evaluate ML/AI models for fault detection, fraud mitigation, and payment optimization.
• Communicate findings to stakeholders and drive data-informed decisions across product and engineering partners.
• Collaborate with stakeholders to shape data and product roadmaps and scale measurement frameworks.
• Continue to improve brand measurement and customer insights through scalable data products.

Skills

Quantitative analysis

Causal inference

Python

R

SQL

Communication

Independent work

Payments Fraud/Risk knowledge

LLM/AI system familiarity

Education

Master’s degree in quantitative field

PhD (advanced degree)

Tools

Python

R

SQL

Job description

Airbnb is seeking a data scientist to lead quantitative measurement for payments, focusing on fraud mitigation and loss optimization. You will develop causal inference frameworks, build ML models, and communicate insights to cross-functional partners to improve platform safety and efficiency.

The role requires deep statistical expertise, experience with end-to-end ML, and the ability to operate in a fast-paced, globally distributed environment. Remote eligibility within the US is available.