Amazon

Lead Applied Scientist

3+ months agoSeattle, WA

DESCRIPTION

How can we use Machine Learning (ML) techniques to build algorithms to better resolve our Selling Partners issues? How can we optimally route phone, email and chat contacts form Selling Partners to improve our Associates occupancy rates? How to leverage ML recommendations to route incoming contacts to the most optimally skilled associates to quickly and successfully resolve the issues that Selling Partners are experiencing, resulting in quicker and successful resolution of the issues sellers experiencing? How can we optimize day-to-day staffing and scheduling in Amazon service centers by leveraging intra-day data on multiple key planning inputs?

The answers to these questions and others like them are core to helping Amazon's Marketplace business thrive and expand, including delivering best-in-the-class experience for our Selling Partners and call center Associates. Our cross-functional team works closely with various stakeholders world-wide such as Finance, Operations, Regional Capacity Planners, Global Planning, Hiring and Training to help them with data-driven business decisions.

Using AWS' large-scale computing resources the Applied Scientist will develop and deploy ML models to match demand (incoming contacts from selling partners) and supply (daily schedules for call center associates) to improve the service levels. The Applied Scientist will work with domain experts and engineers to deploy those ML algorithms into production and continuously improve their performance. The Applied Scientist will interact with the Amazon ML/Optimization community and mentor Scientists and Software Development Engineers with a strong interest in ML. Your work will directly benefit sellers, vendors, brands and associates on the Amazon Marketplace platform. We are looking for a passionate, hard-working, and talented Applied Scientist who has experience in building mission critical, agile and scalable big-data solutions that deliver high-impact results.

Basic Qualifications

- PhD in Computer Science, Industrial Engineering, Mathematics, Statistics or a related quantitative field.
- +5 years of hands-on experience after PhD degree in developing, deploying, iterating, validating and maintaining ML models.
- Programming expertise with Python, including ML related libraries (MXNet, Tensorflow, Torch, scikit-learn, etc.)
- Demonstrated experience in reinforcement learning, unsupervised learning and/or active learning in a commercial setting.
- Experience in building end-to-end large-scale machine-learning models and infrastructure.
- At least 2 years of experience in designing and building scalable technical solutions using cloud computing platforms (e.g., AWS, Azure, Google Cloud).
- Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization.

Preferred Qualifications

The ideal candidate will have a PhD in Computer Science, Industrial Engineering, Mathematics, Statistics or a related quantitative field, and 6+ years of relevant work experience, including:
- Experience applying theoretical ML models using large data sets in production environment.
- Demonstrated experience in delivering low-latency ML components for real-time or performance-critical systems, and distributed/parallel programming (Ray, Dask, Spark, Horovod, MPI, etc.).
- Strong record of publications in some of the following areas: Machine Learning, Deep Learning, Deep Recommender Systems, Deep Reinforcement Learning and Clustering.
- At least 4 years of experience in designing and building scalable technical solutions using cloud computing platforms (AWS).
- Strong personal interest in learning, researching, and creating new technologies with high commercial impact.

We are looking for a passionate, hard-working, and talented Applied Science leader who has experience in building mission critical, agile and scalable big-data solutions that deliver high-impact results

Please visit https://www.amazon.science for more information

BASIC QUALIFICATIONS

- PhD in Computer Science, Industrial Engineering, Mathematics, Statistics or a related quantitative field.
- +5 years of hands-on experience after PhD degree in developing, deploying, iterating, validating and maintaining ML models.
- Programming expertise with Python, including ML related libraries (MXNet, Tensorflow, Torch, scikit-learn, etc.)
- Demonstrated experience in reinforcement learning, unsupervised learning and/or active learning in a commercial setting.
- Experience in building end-to-end large-scale machine-learning models and infrastructure.
- At least 2 years of experience in designing and building scalable technical solutions using cloud computing platforms (e.g., AWS, Azure, Google Cloud).
- Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization.

PREFERRED QUALIFICATIONS

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The ideal candidate will have a PhD in Computer Science, Industrial Engineering, Mathematics, Statistics or a related quantitative field, and 6+ years of relevant work experience, including:
- Experience applying theoretical ML models using large data sets in production environment.
- Demonstrated experience in delivering low-latency ML components for real-time or performance-critical systems, and distributed/parallel programming (Ray, Dask, Spark, Horovod, MPI, etc.).
- Strong record of publications in some of the following areas: Machine Learning, Deep Learning, Deep Recommender Systems, Deep Reinforcement Learning and Clustering.
- At least 4 years of experience in designing and building scalable technical solutions using cloud computing platforms (AWS).
- Strong personal interest in learning, researching, and creating new technologies with high commercial impact.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us