Sr. Applied Scientist, Last Mile Science
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, the WW Amazon Logistics, Business Analytics 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.
We are looking for an enthusiastic, customer obsessed, Sr. Applied Scientist with good analytical skills to help manage projects and operations, implement scheduling solutions, improve metrics, and develop scalable processes and tools. The primary role of an Applied Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on how the final phase of delivery is done at Amazon.
This role requires robust program management skills and research science skills in order to act on research outcomes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment.
Responsibilities
1. Develop input and assumptions based preexisting models to estimate the costs and savings opportunities associated with varying levels of network growth and operations
2. Creating metrics to measure business performance, identify root causes and trends, and prescribe action plans
3. Managing multiple projects simultaneously
4. Working with technology teams and product managers to develop new tools and systems to support the growth of the business
5. Communicating with and supporting various internal stakeholders and external audiences
Minimum Qualifications
1. 6+ years of building machine learning models for business application experience
2. Knowledge of programming languages such as C/C++, Python, Java or Perl
3. Experience programming in Java, C++, Python or related language
4. Experience with neural deep learning methods and machine learning
5. PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
6. 15+ years of relevant, broad research experience
7. Deep expertise in Machine Learning
8. Proficiency in programming
9. Core competency in mathematics and statistics
10. Track record of successful projects in algorithm design and product development
11. Publications at top-tier peer-reviewed conferences or journals
12. Prior experience with mentorship and/or management of scientists
13. Thinks strategically, but stays on top of tactical execution
14. Exhibits excellent business judgment; balances business
15. Effective verbal and written communication skills
16. Experience working with real-world data sets and building scalable models from big data
17. Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow
18. Experience with large scale distributed systems
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