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We are looking for a passionate Staff-level Data Scientist to lead quantitative measurement efforts and bring novel scientific approaches to drive decision making across our platform’s payment experience. This data scientist will perform careful hypothesis generation, causal inference framework development, and model development to ideate and drive payment strategies on our platform.
Job Responsibility:
Inference: Develop and apply causal inference methods, including experimental, econometric regressions, and quasi-experimental methods to measure a wide-range of platform/product impacts
AI/ML: Build methods for robust evaluation of ML/AI model efficiency and performance. Ability to identify use-cases for and develop predictive models to classify, segment, and interpret our users’ behavior
Optimization: Develop methodologies to explore/simulate the impact of new interventions and develop data products to optimize product/operational strategies
Communication: Deliver robust research reports and effective data visualizations. Collaborate with and present to stakeholders to identify opportunities and communicate findings, and drive impact
Empowerment: Think strategically about opportunities to improve and scale our brand measurement and customer insights
Requirements:
9+ years of industry experience in a quantitative analysis role with a Master’s degree in a quantitative field (math / economics / statistics, and etc.), or 6+ years of experience with a PhD degree
Strong knowledge of causal inference, experimentation, and statistical modeling
Skilled in statistical programming (Python or R) and database usage (SQL)
Proven ability to communicate clearly and effectively to audiences of varying technical levels
Ability to translate complex findings and results into compelling narratives that drive impact
Excellent project management, communication, and teamwork skills
Nice to have:
Payments/Risk Domain expertise is a strong plus
What we offer:
bonus, equity, benefits, and Employee Travel Credits
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