Disrupting the way Amazon fulfills our customers’ orders.
Amazon operations is changing the way we improve Customer Experience through
flawless fulfillment focused on 1) successful on-time delivery, 2) at speed
and 3) at the lowest possible cost. Being the engine of Amazon Operational
excellence, driving zero defects through ideal operation, being the heart of
the Fulfillment network and its center of excellence, being proactive and
aspiring for zero defects across the network with 100% organizational
engagement.
For example, our applied science team leverage a variety of advanced machine
learning and cloud computing techniques to power Amazons operations
performance management. This includes building algorithms and cloud services
using LLMs, deep neural networks, and other ML approaches to make root cause
analysis of incidents and defects better. They develop machine learning models
to predict inbound capacity forecasts and select the optimal order of
unloading and stowing the incoming items in the Fulfilment Center. The teams
also utilize Langchain, Amazon Bedrock, Amazon Textract, ElasticCache Redis,
Opensearch and Kubernetes to extract insights from big data and deliver
recommendations to operations managers, continuously improving through offline
analysis and impact evaluation.
Underpinning these efforts are unique technical challenges, such as operating
at unprecedented scale (100k requests per second with SNSSQS and <1ms latency
with Redis) while respecting privacy and customer trust guarantees, and
solving a wide variety of complex computational operational problems related
to inbound management for unloading and stowing before stow time SLA, outbound
for picking and packing before SLAM PAD time and shipping for staging and
loading before Critical Pull Time.
Key job responsibilities
GOX team is looking for a Senior Applied Scientist to support our vision of
giving our customers the best fulfillment experience in the world, and our
mission of delighting our customers by providing capabilities, tools and
mechanisms to fulfillment operations. As Skynet Sr. APSCI, you would be
providing resources and expertise for all data related reports (dashboard,
scorecards…), analysis (statistical approach), and Machine Learning products
and tools development. On top of your internal customers within GOX team you
would be supporting more widely with your experience and skills all across the
org, partnering with a wide range of departments within Ops Integration
(Packaging, Sustainability) within the company mainly with ICQA, ATS, AMZL,
GTS… on several projects. You will be part of the community of Scientists
within Amazon Operations including other AS, BIEs, SDEs, … split across the
different departments. You will be part of projects requiring your close
collaboration and interactions with Operations that require you to have a good
understanding of product flow and process all along the distribution chain.
The GOX team is now recognized for its expertise and excellence in creating
tools that improve massively the customer experience. Several of them now
rolled out in other regions with some of these tools becoming worldwide
standard.
Reporting to the GOX Senior Manager, you will be responsible for developing
the data-driven decision process from historical data and ML based predictive
analysis and maintaining accurate and reliable data infrastructure. You will
work across the entire business, and be exposed to a wide range of functions
from Operations, Finance, Technology, and Change management. The successful
candidate will be able to work with minimal instruction and oversight, manage
multiple tasks and support projects simultaneously. Maintaining your
relationships with the customers in operations and within the team, while
owning deliverables end-to-end is expected. Critical to the success of this
role is your ability to work with big data, develop insightful analysis,
communicate findings in a clear and compelling way and work effectively as
part of the team, raising the bar and insisting on high standards.
About the team
GOX DEA team is the engine of Amazon Operational excellence at the heart of
the fulfillment network operations, aspiring zero defects. It is our purpose
to improve Customer Experience through flawless fulfillment focused on 1)
successful on-time delivery, 2) at speed and 3) at the lowest possible cost.
Our Solutions support on-time delivery of billions of packages to our
customers across the globe leveraging AI & Generative AI technology.
### BASIC QUALIFICATIONS
- Highly technical and analytical, possessing 7+ years of Machine Learning
andor Analytics Systems development and deployment experience, IT systems and
engineering experience, security and compliance experience, etc.
- BS level technical degree required; Computer Science or Mathematics
background preferred.
- Possess significant experience of software development andor IT and
implementationconsulting experience.
- Strong verbal and written communications skills are a must, as well as the
ability to work effectively across internal and external organisations and
virtual teams.
- Ability to understand complex business requirements and render them as
prototype systems with quick turnaround time.
- Experience with implementation and tuning in the Big Data Ecosystem, (such
as EMR, Hadoop, Spark, R, Presto, Hive), ML Platforms (SageMaker, Kubeflow,
Azure Machine Learning, SAS, Domino), and MLOps (model development,
orchestration and deployment, monitoring, optimisation).
- Track record of implementing AWS services in a variety of business
environments such as large enterprises and start-ups.
- Knowledge of foundation infrastructure requirements such as Networking,
Storage, and Hardware Optimisation.
- AWS Certification, eg. AWS Solutions Architect, Developer, or AWS Certified
Machine Learning - Specialty
### PREFERRED QUALIFICATIONS
- Hands on experience leading large-scale big data and analytics projects.
- Hands on experience as a database, data warehouse, big dataanalytics
developer or administrator, or work as a data scientist.
- Hands on experience architecting, deploying and maintaining production
machine learning systems.
- Demonstrated industry leadership in the fields of Big Data processing, Data
Sciences and Machine Learning.
- Deep understanding of data, application, server, and network security
- Experience with Statistics, Machine Learning and Predictive Modelling.
- Working knowledge of modern software development practices and technologies
such as agile methodologies and DevOpsMLOps.
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employing a diverse workforce is central to our success. We make recruiting
decisions based on your experience and skills. We value your passion to
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