Amazon Data Services, Inc.

Technology

Sr.DataScientist,FieldEngineering

$159–215k Seattle, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Sr. Data Scientist, Field Engineering at Amazon Data Services, Inc.. Skills: Data Science, Machine Learning, Infrastructure Analytics, Fleet Performance Modeling. Develop scalable models. Maintain analytical frameworks”

What You'll Achieve.

Improve fleet performance; Improve availability; Improve efficiency; Improve reliability; Drive measurable impact

Industry & Context.

Technology
Problems you'll solve

Problem-solving skills; Root cause analysis; Troubleshooting

What They're Looking For.

Must Have

5+ years experience, Bachelor's degree, SQL proficiency, AWS tech stack knowledge

Nice to Have

PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, dbt Certified

What You'll Do.

Develop scalable models

Maintain analytical frameworks

Measure fleet performance

Predict fleet performance

Apply statistical techniques

Apply machine learning techniques

Extract actionable insights

Identify high-impact opportunities

Formulate quantitative problems

Design data science workflows

Implement data science workflows

Enable repeatable analysis

Enable scalable analysis

Formalize system assumptions

Develop methods for deviations

Identify improvement opportunities

Build self-service datasets

Build reporting mechanisms

Provide recommendations

Articulate decision points

Collaborate with applied science teams

Collaborate with software engineering teams

Collaborate with data engineering teams

Ensure model integration

How You'll Work.

Team & Collaboration

Cross-functional teams; Field Engineers; Operations teams; Commissioning teams; Construction teams; Engineering teams; Program managers; Applied science teams; Software engineering teams; Data engineering teams

Communication Scope

Written communication; Verbal communication; Translating findings; Executive presentations; Data-driven recommendations

Process & Methodology

Roadmap planning

Full Job Description

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. The Data Center Field Engineering Team is the engineering owner for the lifecycle of AWS data center mechanical and electrical infrastructure. This includes supporting new designs and innovations through data center end-of-life, with a focus on root cause analysis of failures, capacity and availability improvement, and optimization of the existing fleet. As a Senior Data Scientist on the Field Engineering Portfolio team, you will bring advanced analytical and machine learning capabilities to one of the most critical infrastructure organizations at AWS. You will develop scalable models and data-driven frameworks that measure, predict, and improve fleet performance — including data center availability, operational efficiency, and key performance indicators (KPIs) across the global AWS data center fleet. You are an exceptionally strong communicator, both written and verbally, capable of translating complex quantitative findings into clear recommendations for senior engineering and business leadership.

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