Description

Our mission is to help every vendor drive the most significant impact selling on Amazon. Our team invent, test and launch some of the most innovative services, technology, processes for our global vendors.

Amazon is looking for a talented and passionate Senior Applied Scientist to build world class statistical and machine learning models to understand our vendors and help them grow. They’ll be comfortable with ambiguity and enjoy working in a fast-paced and dynamic environment. The position also requires collaboration with other scientists within the team and worldwide, Product Managers and Software Developers. Our current projects touch on the areas of causal inference, representation learning, anomaly detection, NLP and forecasting.

We place strong emphasis on continuous learning through internal mechanisms for our scientists to keep on growing their expertise and keep up with the state of the art. Our goal is to be primary science team for vendor solutions in Amazon, worldwide.

Key job responsibilities

The Senior Applied Scientist is accountable for:

(1) creating a roadmap of the most challenging business questions from our leading vendors and use data to articulate possible root cause analysis and solutions.

(2) work closely with other research scientists, machine learning experts, and economists in 3 countries to design and run experiments, research new algorithms, and find new ways to improve vendor analytics, prove incrementality and drive growth.

(3) The Scientist will partner with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our vendors.

(4) Understanding drivers, impacts, and key influences on vendor growth dynamics.

(5) Drive actions at scale to provide high impact services for vendors using scientifically-based methods and decision making and driving a low cost to serve.

(6) Helping to build production systems that take inputs from multiple models and make decisions in real time.

(7) Automating feedback loops for algorithms in production.

(8) Utilizing Amazon systems and tools to effectively work with terabytes of data.

About the team

JP Retail Science is a team of Applied Scientists, Science Managers, and Business Intelligence Engineers. The team's charter is to develop science-based models to help all Amazon vendors to maximize their growth. From our base office in Tokyo, Japan, we build for all vendors worldwide, and collaborate with other science teams in Europe and US.

Because we are not tied to a specific technology, such as Search or Alexa, our projects and the science required change dynamically depending on the vendor needs. In the past we have worked on initiatives drawing from multiple disciplines, including causal inference, LLM, forecasting, and optimization.

A large fraction of the team consists of former academic researchers, and we maintain that culture through collaboration with universities, exchange programs, and conference participation.

We are open to hiring candidates to work out of one of the following locations:

Tokyo, 13, JPN

Basic Qualifications

• 5+ years of building machine learning models for business application experience

• PhD, or Master's degree and 5+ years of applied research experience

• Experience programming in Java, C++, Python or related language

• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

• Experience with large scale distributed systems such as Hadoop, Spark etc.

Please check the website below for measures to eliminate unwanted second-hand smoking in each facility:

https://www.amazon.jobs/en/landing_pages/passivesmoking

就業の場所における受動喫煙を防止するための措置に関する事項については、下記リンク先をご覧ください。

https://www.amazon.jobs/jp/landing_pages/passivesmoking

The salary information can be provided individually prior to the 1st interview

賃金に関する条件は、１次面接の前に個別にご案内することができます