Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment.
We need an expert in econometric and statistical tools to extract insights at scale by building models with our world class data systems, designing advanced new experimental methods, and investigating complex behavioral patterns.
The Amazon Search team creates powerful, customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, our services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide.
Within Amazon Search, the Data Science team brings expertise in constrained optimization, modeling data, and experimental methods. We partner with internal and external teams to bring data to active projects in addition to pioneering new insights, measurement and testing methodologies, and optimization strategies. This ensures the proper scientific use of data in launch decisions and that we are properly optimizing all trade-offs in product design. In addition to working with partners, we incubate new modeling techniques, and perform 'front line recon' on potential new models and tools.
Scientists at Amazon are expected to develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems around the company. Major responsibilities include:
Measure / Quantify / Expand:
· Design, size, and analyze field experiments at scale.
· Apply econometric or statistical knowledge to improve Amazon Search (using machine learning techniques is a plus)
· Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.
· Analyze historical data to identify trends and support decision making.
Explore / Enlighten
· Formalize assumptions about how Amazon Search is expected to work.
· Given anomalies, whether anecdotal or identified automatically, deep dive to explain why they happen, and identify fixes.
Decide / Recommend
· Build decision-making models and propose solution for the business problem you defined
· Analyze A/B tests and recommend ways to making them faster and more robust
· Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
· Utilize code (python or another object oriented language) for data analyzing and modeling algorithm
· PhD in Economics, Statistics, Finance or related field
· At least 2 years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, Stata, Matlab)
· Experience articulating business questions and using quantitative techniques to arrive at a solution using available data
· Applicants with more experience, including mid-career, are also strongly encouraged.
· Strong background in statistics methodology, applications to business problems, and/or big data.
· Ability to work in a fast-paced business environment.
· Strong research track record.
· Effective verbal and written communications skills.
· Experience processing, filtering, and presenting large quantities (Millions to Billions of rows) of data
· Experience designing experiments, and ability to infer causal relationships
· 1-2 years of experience in industry, consulting, government or academic research