Applied Scientist, Amzn Shipping-Prd & Tech, Amzn Shipping-Prd & Tech

Amazon; Seattle (WA); Remote; USD 95,000 - 145,000; Full time

Job summary

An established industry player is seeking Applied Scientists to tackle complex machine learning challenges in package logistics. In this role, you will develop models that enhance transportation efficiency, predict delivery delays, and improve cost auditing processes. You will leverage various machine learning techniques, including supervised and unsupervised learning, to translate business problems into scalable ML solutions. Join a vibrant team of data scientists and engineers, where your contributions will directly impact customer experience and operational excellence. If you are passionate about machine learning and eager to make a difference, this is the opportunity for you.

Qualifications

• Experience in programming languages like Java, C++, or Python.
• Strong background in machine learning and algorithms.

Responsibilities

• Build ML models to optimize package movement and cost auditing.
• Collaborate with diverse teams to enhance ML solutions.

Skills

Java

C++

Python

Algorithms and Data Structures

Data Mining

Numerical Optimization

High-Performance Computing

Communication Skills

Education

PhD

Master's Degree

Tools

Unix/Linux

Job description

Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network.

Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be picked from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications.

Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services.

You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements.

If you are excited by this charter, come join us!

BASIC QUALIFICATIONS

- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

PREFERRED QUALIFICATIONS

- Experience using Unix/Linux
- Experience in professional software development
- PhD, or a Master's degree and experience building machine learning models or developing algorithms for business application
- Significant peer reviewed scientific contributions in relevant field
- Extensive experience applying theoretical models in an applied environment
- Expertise on a broad set of ML approaches and techniques
- Prior Experience in Transportation Logistics business
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit this link for more information.

Location: USA, WA, Virtual Location - Washington

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