Amazon EU Sarl
Data Science, Science, Logistics
DataScientistI
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Scientist I at Amazon EU Sarl. Skills: Large Language Models, Generative AI, Predictive analytics, Data science. Lead development and delivery of core data science. Define analytical approaches”
What You'll Achieve.
Drive measurable operational improvements; Improve operational excellence; Create a virtuous cycle of AI-enablement
Industry & Context.
Root cause analysis; Troubleshooting; Analytical approaches; Complex problems; Ambiguous problems; Diagnostic problems
What They're Looking For.
Must Have
Experience with data scripting languages (SQL, Python, R), Experience as a data/research scientist, statistician or quantitative analyst
Nice to Have
Knowledge of statistical packages and business intelligence tools, Experience with clustered data processing (Hadoop, Spark, Map-reduce, Hive)
What You'll Do.
Lead development and delivery of core data science
Define analytical approaches
Drive solution architecture
Spearhead data science best practices
Assess and select ideal solution approaches
Apply deep expertise to problems
Own and deliver end-to-end data science solutions
Build a track record of successful launches
Work closely with operations business teams
Translate ambiguous needs into problem statements
Take the lead on large
cross-functional data science
Influence change across multiple teams
Build consensus among discordant views
Align stakeholders on the right path forward
Make sound scientific and technical trade-offs
Advocate for the right measurements
Stay current on data science developments
Raise awareness of new techniques
Lead knowledge-sharing sessions
Mentor data scientists
Drive data science best practices
Lead initiatives to improve operational
Identify blind spots in current metrics
Challenge assumptions
Restructure data sources
Partner with engineering and AI/ML teams
Integrate data science solutions
Contribute to strategic planning
Advise senior leadership on AI investment priorities
Advise senior leadership on data science strategy
How You'll Work.
Team & Collaboration
Cross-functional teams; Partner SMEs
Full Job Description
As part of the AI Operations Integration team, we're passionate about pushing the boundaries of AI and transforming how operations teams work. We are looking for an entrepreneurial, experienced, creative, and AI-Native Data Scientist I to join our team. As a Data Scientist I on the AI Operations Integration team, you'll have the opportunity to work on exciting, ambiguous problems that combine Large Language Models (LLMs), Generative AI, and predictive analytics to create intelligent, data-driven operational solutions that fundamentally change how work gets done across Amazon's global operations footprint. You will be responsible for leading the development and delivery of core data science capabilities that power AI-enabled operations. You will have significant influence on our overall strategy by defining analytical approaches, driving solution architecture, and spearheading the data science best practices that enable a high-quality, scalable AI ecosystem. In this role, you'll collaborate with a diverse team of software engineers, AI/ML specialists, operations experts, and technical program managers to develop novel solutions that advance the state of the art in AI-enabled operations. You'll leverage Amazon's vast data resources and computing infrastructure to accelerate development and drive innovation. Your contributions will help define our overall data science strategy, from data enrichment and model optimization to system architecture and best practices, creating a virtuous cycle of AI-enablement that continuously improves operational excellence. Key job responsibilities - Assess and select ideal solution approaches from a wide range of data science methodologies, including machine learning, statistical modeling, NLP, and LLM-based techniques, to solve complex, ambiguous operational problems with significant business impact. - Apply deep expertise to problems involving complex interactions among software systems, data pipelines, and operational processes; desi
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