Amazon EU Sarl
Technology
Manager,DataScience
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optimal for Manager candidates.
“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.
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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