Sr. Applied Scientist - Global Operational Excellence
Job ID: 2711454 | Amazon UK Services Ltd. - A10
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 Amazon's 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 Fulfillment 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 SNS/SQS 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
The GOX team is looking for a Senior Applied Scientist to support our vision of giving our customers the best fulfillment experience in the world. 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. You will support internal customers within the GOX team and partner with a wide range of departments within Ops Integration (Packaging, Sustainability) 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 involved in projects requiring close collaboration and interaction with Operations that necessitate a good understanding of product flow and process along the distribution chain. The GOX team is recognized for its expertise and excellence in creating tools that significantly improve the customer experience.
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 relationships with 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 clearly, and work effectively as part of the team, raising the bar and insisting on high standards.
About the team
The 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 and/or Analytics Systems development and deployment experience, IT systems and engineering experience, security and compliance experience.
- BS level technical degree required; Computer Science or Mathematics background preferred.
- Significant experience of software development and/or IT and implementation/consulting experience.
- Strong verbal and written communication 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, e.g., 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 data/analytics 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 DevOps/MLOps.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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/content/en/how-we-hire/accommodations.
Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
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