Data Scientist 新卒採用2026 , LMEA Science

- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or Master's degree
- Speak, write, and read fluently in Japanese
- Speak, write, and read fluently in English
- ML Python skills (scikit-learn, scipy, pytorch / keras / tensorflow, prophet, XGboost)
- Python optimization libraries (xpress)
- Familiarity with SQL (Redshift, PostgreSQL)
Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast?
Have you wondered where it came from and how much it cost Amazon to deliver it to you?
If so, Amazon Logistics (AMZL), Last Mile team is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner to deliver a smile for our customers.

As part of Amazon Last Mile Execution Analytics organization, the Data Scientist will work closely with other research scientists, machine learning experts, and economists to design and run experiments, create analyses, carry over solutions from other regions, and find new ways to improve last mile analytics to optimize the Customer experience. 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 customers. They also work on cross-disciplinary, cross-regions efforts with other scientists within Amazon.

We are seeking candidates with robust skills in Optimization modeling (Mixed Integer Programming, Dynamic Programming, Decomposition Methods), Python coding, data collection, and analysis. Background in Machine Learning or Economics would be advantageous. The ideal candidate should possess the ability to interpret regression model coefficients in non-mathematical terms, familiarity with various probability distributions, and the capability to elucidate how actions taken by business partners influence their desired outcomes. Strong communication skills to articulate complex analytical concepts to non-technical stakeholders in English and Japanese are essential.

Application process:
Submit your resume in English by Oct 21 18:00 (After this time application window will be closed.)
If you have portfolio of data science projects (thesis, papers, school projects, Kaggle competitions, Github) please add to your resume.

Recruiting Process (Online):
1st interview
Final interviews (x 3)

Key job responsibilities
• Design and develop advanced mathematical optimization models and apply them to define strategic and tactical needs, driving appropriate business and technical solutions in areas such as routing planning, supply chain optimization, and network optimization.
• Develop time series forecasting, machine learning, and deep learning models, research, prototype, simulate, and experiment with these models using modeling languages like Python, and participate in production-level deployment.
• Create, enhance, and maintain technical documentation for models and solutions.
• Present and effectively communicate complex analytical concepts to other Scientists, Product and Software Engineering teams, as well as Stakeholders.
• Lead project plans from a scientific perspective by managing product features, technical risks, milestones, and launch plans, ensuring seamless collaboration across cross-functional teams.