Amazon EU Sarl

Data Science, Science, Logistics

DataScientistI

€105–145k ~AI est. Luxembourg, Luxembourg FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“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.

Data Science, Science, Logistics
Problems you'll solve

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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