The Selection team decides what is being sold by Amazon.com. As one component of the famous Amazon Flywheel, Selection is strategically important to our topline growth. We are responsible for thought leadership and innovation to improve the existing and develop new solutions for optimizing Amazon’s selection, better serving our customers. We build the models to make these selection decisions, driven by signals such as historical search and sales data, understanding of item economics, and product substitutability and complementarity.
You will partner with scientists, economists and engineers to propose, prototype, analyze, implement and deliver to production a variety of data science initiatives. You will develop a comprehensive understanding of Amazon’s business and supply chain processes and make use of rich data to make inferences about customer behavior. You will propose, analyze and communicate the results of experiments that measure causal effects of selection changes with great autonomy. You will define, create and beautifully present metrics that deepen our understanding of how customers interact with our selection. You will creatively translate our collected data into initiatives with measurable impacts on customer satisfaction and business growth. You will define team data science processes and mentor your colleagues in the art of data science.
In Amazon, everything operates at world scale. You will gain hands-on experience with big data technologies that handle the volume, development processes that supply the robustness, and recent modeling techniques that cut through the complexity. You will be inspired by and participate in the rich scientific community centered around Amazon’s unparalleled universe of econometric questions.
- 5 or more years of experience in industry research and development; or equivalent academic experience
- Master's in Computer Science, Statistics, Operations Research or related field
- Experience with causal inference, econometrics, or inferential statistics
- Fluency in Python, R, or other scientific computing language
- Excellent communication skills, oral and written, and ability to work collaboratively
- Independence and agility in developing prototype code under ambiguity
- PhD in Computer Science, Statistics, Operations Research or related field - Experience with causal inference, econometrics, or inferential statistics
- Experience in supply chain optimization and/or operations research
- Experience defining metrics and data science processes
- Experience with optimization software like CPLEX, Xpress or Gurobi
- Research track record in area relevant to business data science