Applied Scientist II, Geospatial Science, Last Mile

Amazon; London; On-site; GBP 50,000 - 100,000; Full time

Job summary

Join a forward-thinking company as an Applied Scientist II in Geospatial Science. This role involves tackling complex business challenges through innovative machine learning solutions that directly impact delivery planning. You will collaborate with a talented team, leveraging state-of-the-art technologies and contributing to meaningful research. With a focus on developing scalable models and algorithms, you'll have the opportunity to publish your findings in prestigious conferences, enhancing your professional growth. If you're passionate about machine learning and eager to make a difference, this is the perfect opportunity for you.

Qualifications

• 3+ years of experience in building ML models for business applications.
• Experience in patents/publications at top-tier conferences.

Responsibilities

• Deliver on complex business problems using machine learning techniques.
• Explore and implement SOTA technologies for business applications.

Skills

Machine Learning

Natural Language Processing

Algorithms and Data Structures

Numerical Optimization

Data Mining

Parallel and Distributed Computing

High-Performance Computing

Communication Skills

Education

Master's Degree

PhD

Tools

Java

C++

Python

Unix/Linux

Job description

Applied Scientist II, Geospatial Science, Last Mile

Customer addresses, Geospatial information and Road-network play a crucial role in Amazon Logistics' Delivery Planning systems. We own exciting science problems in the areas of Address Normalization, Geocode learning, Maps learning, Time estimations including route-time, delivery-time, transit-time predictions which are key inputs in delivery planning. As part of the Geospatial science team within Last Mile, you will partner closely with other scientists and engineers in a collegial environment to develop enterprise ML solutions with a clear path to business impact. The setting also gives you an opportunity to think about a complex large-scale problem for multiple years and build increasingly sophisticated solutions year over year. In the process, there will be opportunities to innovate, explore SOTA and publish the research in internal and external ML conferences.

Successful candidates will have deep knowledge of competing machine learning methods for large scale predictive modelling, natural language processing, semi-supervised & graph based learning. We also look for the experience to graduate prototype models to production and the communication skills to explain complex technical approaches to stakeholders of varied technical expertise.

Key job responsibilities

As an Applied Scientist II, your responsibility will be to deliver on a well-defined but complex business problem, explore SOTA technologies including GenAI and customize the large models as suitable for the application. Your job will be to work on an end-to-end business problem from design to experimentation and implementation. There is also an opportunity to work on open-ended ML directions within the space and publish the work in prestigious ML conferences.

About the team

LMAI team owns WW charter for address and location learning solutions which are crucial for efficient Last Mile delivery planning, who also owns problems in the space of maps learning and travel time estimations.

BASIC QUALIFICATIONS

- 3+ years of building machine learning models or developing algorithms for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 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
- Master's degree, or PhD

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