Data Scientist Amazon
Seattle, WA

Job Description

Are you passionate to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions to help Selling Partners and Customers on Amazon? The Selling Partner Recruitment and Development team seeks to recruit all the brands in the world to sell on Amazon, while empowering them to grow their business and provide a great customer experience. Selling on Amazon is one of the fastest growing businesses at Amazon.com and empowers millions of entrepreneurs worldwide. Our team will invent and innovate across technology, processes and people to grow the program, improve engagement and satisfaction and enable scalable solutions.

We are looking for a Data Scientist to lead us to identify opportunities and build scalable solutions to enable a world-class level fulfillment network for Selling Partners. As a successful data scientist on our talented team of scientists and engineers, you will identify specific and actionable opportunities to solve business problems, and collaborate with engineering, research, and business teams for future innovation. You need to understand e-commerce domain knowledge and the meanings of data. You need to be a sophisticated user of advanced quantitative techniques and data visualization for answering specific business questions, and an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication.

Major responsibilities include:

Translate / Interpret

Translate ambiguous business questions and concerns into specific quantitative questions that can be answered with available data using sound methodologies.

Measure / Quantify/Expand

a. Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.

b. Analyze historical data to identify trends and support decision making.

c. Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.

d. Provide requirements to develop analytic capabilities, platforms, and pipelines.

e. Apply statistical or machine learning knowledge to specific business problems and data.

Explore / Enlighten

a. Formalize assumptions, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed.

b. Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.

Make Decisions or Recommendations

a. Build decision-making models and propose solution for the business problem you defined

b. Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.

Utilize code (python, R or other statistical software) for statistical data analyzing and modeling algorithms