Amazon Science Manager LMEA 

Japan 

80492612

Key job responsibilities
As a Science Manager within JP AMZL LMEA team, you will lead a team of data and research scientists towards designing and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, optimization models and graph models. You will have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best program managers, research scientists, data scientists, engineers, and economists to execute on JP AMZL Science vision and prepare scientific work for production systems integration. You will bring deep technical expertise in the area of Machine Learning and optimization. Other responsibilities include:* Lead a team of data and research scientists towards design, development and evaluation of highly innovative ML/optimization models for solving complex business problems.
* Technically lead and mentor the scientists on the team.
* Research and apply the latest ML techniques and best practices from both academia and industry.
* Use and analytical techniques to create scalable solutions for business problems.
* Work closely with BI and data engineers to build relevant pipelines for your models at large scale.
* Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.A day in the life

- 5+ years of building quantitative solutions as a scientist or science manager experience
- 2+ years of scientists or machine learning engineers management experience
- 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Knowledge of Python or R or other scripting language

- Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
- Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems
- PhD
- Japanese language ability