Applied Scientist II

Job description

DESCRIPTION

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, A9 Product Search 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 Relevance team has a mission to help customers efficiently find anything they are looking for. This charter requires us to build innovative ranking solutions across very diverse categories, with an amazonian focus on our customers and on the long-term. We dive deep to figure out idiosyncrasies of how customers shop for groceries, make purchase decisions for their business, browse videos, or choose e-books to read, then we turn these learnings into innovative machine learned ranking solutions to improve customer satisfaction and business metrics.

In this role you will leverage your strong statistical background to help build the next generation of our ranking model development and assessment pipeline, harnessing and explaining rich data at Amazon scale, and providing automated insights to improve machine learned rankers that impact millions of customers every day. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience with machine learning models and information retrieval systems at scale. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.

Desired profile

BASIC QUALIFICATIONS

· Masters degree in Statistics, Mathematics or related field, or equivalent experience.
· A strong ability in statistical modeling and analysis to provide rigorous solutions that address business needs.
· Excellent data visualization and written communication skills to translate complex models and analysis results into layman terms.
· Hands on development experience in C++, Java, or other OOP language.
· Experiencing with programming in R, MATLAB, Python or similar scripting languages.
· Experience with data visualization technologies, including interactive visualization (i.e. D3js, Bokeh, Matplotlib, FusionCharts, or HighCharts).
· Knowledge of Information Retrieval theory and practice.