Applied Scientist, Last Mile Geospatial Science
1 week ago
Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
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 building increasingly sophisticated solutions year over year. In the process there will be opportunity to innovate, explore SOTA and publish the research in internal and external ML conferences.
Here is a glimpse of the problem spaces and technologies that we deal with on a regular basis:
1. De-duping and organizing addresses into hierarchy while handling noisy, inconsistent, localized and multi-lingual user inputs. We do this at the scale of millions of customers for established (US, EU) as well as emerging geographies (IN, MX). We make use of technologies like LLMs, Weak supervision, Graph-based clustering & Entity matching. We also use additional modalities such as building outlines in maps, street view images and 3P datasets, gazetteers.
2. Build a generic ML framework which leverages relationship between places to improve delivery experience by learning precise delivery locations and propagating attributes, such as business hours and safe places.
3. (Work done in sister teams) Developing systems to consume inputs from areal imagery and optimize our maps to enable efficient delivery planning. Also building models to estimate travel time, turn costs, optimal route and defect propensities.
Key job responsibilities
About the team
Last Mile Address Intelligence (LMAI) team owns WW charter for address and location learning solutions which are crucial for efficient Last Mile delivery planning. The team works out of Hyderabad and Bangalore offices in India. LMAI is a part of Geospatial science team, which also owns problems in the space of maps learning and travel time estimations. The rest of the Geospatial science team and senior leadership of Last Mile org works out of Bellevue office.
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
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Bangalore, Karnataka, India Amazon Full timeDESCRIPTIONCustomer 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...
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Bengaluru, India Amazon Full timeAmazon's Last Mile Analytics and Quality team is seeking an experienced program manager to lead program(s) and/or escalations management for the space of worldwide voice of customers in the Amazon Geospatial domain. In this vertical, we drive initiatives by partnering with various teams in Last Mile to reduce delivery defects while improving Last Mile...
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Bengaluru, India Amazon Full timeAmazon’s Last Mile Analytics and Quality team is seeking an experienced program manager to lead program(s) and/or escalations management for the space of worldwide voice of customers in the Amazon Geospatial domain. In this vertical, we drive initiatives by partnering with various teams in Last Mile to reduce delivery defects while improving Last Mile...
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