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AirbnbAirbnbUnited States

Senior Data Scientist - Payments

The data scientist will lead causal inference, experimentation, statistical modeling, and machine-learning efforts to optimize payments, mitigate fraud, and guide product strategy. The role requires 5+ years of quantitative industry experience with a master’s degree, or 3+ years with a PhD.

179k – 210k/yr
Remote5+ YOEData Science

About the role

Responsibilities

  • Lead quantitative measurement efforts and develop scientific approaches to guide payment decisions.
  • Generate hypotheses, develop causal inference frameworks, and build and evaluate models for payment strategies.
  • Focus on payments fraud mitigation and loss optimization.
  • Develop and apply causal inference methods, including experiments, econometric regressions, and quasi-experimental methods.
  • Build methods to evaluate ML and AI model efficiency and performance.
  • Identify use cases for predictive models to classify, segment, and interpret user behavior.
  • Support evaluation and optimization of agentic and LLM-based systems.
  • Develop methodologies to simulate the impact of interventions and create data products that optimize product and operational strategies.
  • Produce research reports and data visualizations.
  • Collaborate with stakeholders, communicate findings, identify opportunities, and drive data and product roadmaps.
  • Improve and scale brand measurement and customer insights.

Requirements

  • 5+ years of industry experience in a quantitative analysis role with a master's degree in a quantitative field such as mathematics, economics, or statistics; or 3+ years of experience with a PhD.
  • Strong knowledge of causal inference, experimentation, applied statistical modeling, and end-to-end machine learning development.
  • Experience with statistical programming in Python or R and database usage with SQL.
  • Track record of owning a business or technical domain end-to-end, setting a roadmap, serving as an accountable expert, and driving problems to resolution.
  • Ability to communicate clearly and effectively with audiences of varying technical levels.
  • Ability to work independently, set a roadmap, and drive cross-functional alignment.

Nice-to-haves

  • Payments fraud or risk domain expertise.
  • Experience evaluating agentic or LLM-based systems, including decision-quality measurement and human-in-the-loop calibration.

Compensation and Benefits

  • Base pay range: $179,000–$210,000 USD.
  • May be eligible for bonus, equity, benefits, and Employee Travel Credits.

Skills

Causal InferenceExperimentationStatistical ModelingMachine LearningPythonRSQLeconometricsquasi-experimental methodspredictive modelingData Visualizationllm evaluationfraud risk

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