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 Amazon’s 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 business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you. We’re 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 systems. In 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 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

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 Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their team, and their career.

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