Applied Science Manager, LMEA

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 Amazons customers achieving on-time delivery in a cost-effective manner to deliver a smile for our customers.

As Amazon continues to build and expand the first party delivery network this role will be critical to realize this vision. Your team and tech solution will have large impacts to the physical supply chain of Amazon and play a key role in improving Amazon consumer businesss long-term profitability. If you are interested in diving into a multi-discipline high impact space this is the team for you. Were looking for a passionate results-oriented and inventive Scientist who can lead from the front towards developing and deploying ML models for our outbound transportation planning addition you will be working on design development and evaluation of highly innovative ML models for solving complex business problems in the area of outbound transportation planning systems.

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 deploying solutions that will likely draw from a large range of scientific areas such as supervised semi-supervised 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 by working on some of the most difficult problems in the industry with some of the best technical 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 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
In this critical role you will be a technical leader in operations research or machine learning with significant scope impact and visibility. Your solutions have the potential to drive millions of dollars in impact for Amazon last mile business in Japan and other regions. As a science manager on the team you will engage in all facets of the process from ideation business analysis and scientific research to development and deployment of advanced models. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. A successful candidate is able to quickly approach large ambiguous problems turn high-level business requirements into mathematical models identify the right solution approach and prepare contribution to the software development for production systems. Successful candidates must thrive in fast-paced environments which encourage collaborative and creative problem solving be able to measure and estimate risks constructively critique peer research and align research focuses with the Amazons strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves their team and their career.

- 3 years of scientists or machine learning engineers management experience
- Knowledge of ML NLP Information Retrieval and Analytics
- PhD
- Knowledge of machine learning approaches and algorithms
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle including coding standards code reviews source control management build processes testing certification and livesite operations

- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems especially involving deep learning machine learning and computer vision that have been successfully delivered to customers
- Japanese language ability

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