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Data Scientist, Last Mile Execution Analytics (LMEA)

Job ID: 2325578 | Amazon Japan G.K.


The Amazon Logistics (AMZL) Team is responsible for the acquisition, design, construction, and management of all facilities in the Amazon Delivery Station Network.

AMZL is looking for a talented and passionate Data Scientist to help shape its Last Mile business with technical strategies and solutions, by processing, analyzing and interpreting huge data sets. You should be comfortable with ambiguity, problem solving and enjoy working in a fast-paced, diverse and dynamic environment. Using analytical rigor and statistical methods, you mine through data to identify opportunities for Amazon and our delivery channels. And you collaborate with other scientists, engineers, Product and Program Managers to deploy new products and solutions.

[More Information]
Last Mile Department
Data Analyst/BI Engineer
Tokyo Office

*Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, visit

Key job responsibilities

  • Creating a roadmap of the most challenging business questions and use data to articulate possible root cause analysis and solutions
  • Managing and executing entire projects or components of large projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights
  • Partnering with Product, Program and Engineering teams to design and run models, research new algorithms, and prove incrementality and drive growth
  • Understanding drivers, impacts, and key influences on seller growth dynamics
  • Developing and scaling end-to-end ML Models and solutions
  • Automating feedback loops for algorithms in production
  • Utilizing Amazon systems and tools to effectively work with terabytes of data

About the team
Last Mile Execution Analytics (LMEA) team of JP works as an integral part of Amazon Logistics to ensure that its business intelligence, analytics, tools and planning needs are met. By providing information, insight, and decision support, we strive to enable success of all parts of AMZL. Our customer set includes senior management, station operations, external vendors, long-term planning, Ops technology (Voice of the Delivery Station, Voice of the Customer), network planning, and pretty much every BI and Ops teams.

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  • Bachelor or Master's degree in highly quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience
  • 4+ years of experience working in data science in a consumer product company
  • Ability to build and scale ML models
  • Experience coaching junior members to a successful career track
  • Experience in SQL, Excel/VBA, R, Python, or other scripting languages
  • Experience conveying rigorous mathematical concepts and considerations to non-experts through data visualizations
  • Business level of English


  • Masters or PhD in a quantitative field (Computer Science, Economics, Mathematics, Machine Learning, AI, Statistics, or equivalent)
  • 8+ years of experience working in data science in a consumer product company
  • Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval
  • Skilled with Java, C++, or other programming language, as well as with R, SAS, MATLAB, Python or similar scripting language
  • Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
  • Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes
  • Excited about working in a diverse group and contributing to an inclusive culture

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

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