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Tier-1 employer, popular mid-level ML role in metro with broad skill requirements increases competition.
Applied econometrics and fee/P&L domain knowledge moderate transferability despite core ML skill relevance.
Multiple explicit years requirements and a Master's degree requirement make shortlisting strict.
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Translate complex and ambiguous fee-related business challenges into quantifiable scientific problems with measurable impact.
Design, develop, and deploy econometric, AI, and machine learning models to improve measurement, prediction, and planning of Amazon's fee revenue and other P&L elements.
Partner with finance and fee strategy teams to formulate scientific approaches, communicate results, validate models with rigorous simulations, and productionalize scalable solutions.
Minimum 2 years experience as a data scientist.
Minimum 3 years experience in data querying (e.g. SQL) and scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab).
Minimum 3 years experience with machine learning/statistical modeling and data analysis tools.
Master's degree in Science, Technology, Engineering, or Mathematics (STEM) or relevant STEM work experience.
Experienced at applying theoretical models and econometrics in applied, large-scale environments with measurable business impact.
Able to work cross-functionally with finance and strategy teams to translate scientific insights into business decisions and scalable production systems.
Experienced in guiding or mentoring researchers and comfortable communicating complex scientific concepts to cross-functional and external audiences.