Amazon EU Sarl

Technology

Manager,DataScience

€130–185k ~AI est. Luxembourg, Luxembourg FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Manager candidates.

The Brief

“Manager, Data Science at Amazon EU Sarl. Skills: Data Science, Machine Learning, ASIN Classification, People Management. Lead and manage a team of Applied Scientists,. Foster a culture of innovation, scientific rigor, and”

What You'll Achieve.

Deliver accurate, scalable classification solutions; Ensure continuous improvement; Ensure zero-disruption deployments; Ensure data quality standards; Ensure robust experimentation practices

Industry & Context.

Technology
Problems you'll solve

Problem framing; Translate ambiguous challenges

What They're Looking For.

Must Have

Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field, or PhD, 8+ years of experience in data science or applied machine learning, 3+ years in a people management role, Knowledge of Machine Learning and LLM fundamentals, Proven track record of leading teams that deliver ML solutions at scale in production environments, Programming proficiency in Python and SQL, Familiarity with big data technologies (Spark, AWS services)

Nice to Have

Familiarity with compliance and regulatory classification frameworks

What You'll Do.

Lead and manage a team of Applied Scientists

Foster a culture of innovation

Define the team's science roadmap

Prioritize classification initiatives across compliance programs

Own end-to-end delivery of classification solutions

Develop data strategy

Drive architecture decisions

Engineer features from product catalogs

Define evaluation metric frameworks

Translate compliance challenges into data science and ML

Collaborate with business teams

Convert business requirements into scalable ML solutions

Establish classification metrics

Monitor classification metrics

Monitor model performance KPIs

Monitor production health dashboards

Ensure continuous improvement

Partner cross-functionally with Science

Align science investments with business priorities

Build scalable data environments

Support model training

Support model evaluation

Support shadow testing

Support production inference at scale

Mentor and develop team members

Provide career coaching

Provide technical guidance

Provide structured growth plans

Communicate complex technical concepts effectively to non-technical stakeholders

Drive operational rigor

Ensure zero-disruption deployments

Ensure data quality standards

Ensure robust experimentation practices

Stay current with latest research

Apply techniques to production systems

How You'll Work.

Team & Collaboration

Business teams; Science teams; Engineering teams; Product teams; Operations teams; Non-technical stakeholders; Senior leadership

Communication Scope

Communicate complex technical concepts

Process & Methodology

Roadmap planning

Full Job Description

Are you passionate about solving complex classification challenges at massive scale? We are seeking a Data Science Manager to join our ASIN Classification team within WAVE (World Wide AI Enablement). In this high-impact role, you will lead a team of scientists and engineers to architect, deploy, and operationalize advanced machine learning models that drive ASIN classification across a range of compliance programs. From supervised and unsupervised ML approaches to Large Language Models and Small Language Models, you will guide your team in harnessing state-of-the-art techniques to deliver accurate, scalable classification solutions for millions of ASINs. Key job responsibilities • Lead and manage a team of Applied Scientists, Data Scientists, and Engineers, fostering a culture of innovation, scientific rigor, and operational excellence • Define the team's science roadmap and prioritize classification initiatives across compliance programs • Own end-to-end delivery of classification solutions from problem framing and data strategy through model deployment and production monitoring • Drive architecture decisions including model selection, feature engineering from product catalogs, and evaluation metric frameworks • Translate ambiguous, large-scale compliance challenges into well-scoped data science and ML workstreams • Collaborate with business teams to convert business requirements into scalable ML solutions • Establish and monitor classification metrics, model performance KPIs, and production health dashboards to ensure continuous improvement • Partner cross-functionally with Science, Engineering, Product, and Operations teams to align science investments with business priorities • Build scalable data environments and ML pipelines to support model training, evaluation, shadow testing, and production inference at scale • Mentor and develop team members through career coaching, technical guidance, and structured growth plans • Communicate complex technical concepts ef

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