Manager, Data Science, WAVE Science (AI)

TL;DR

Manager, Data Science (AI): Leading the ASIN Classification team to architect and deploy advanced ML models for compliance programs with an accent on scalable classification and multi-modal learning. Focus on translating ambiguous compliance challenges into ML workstreams and managing the end-to-end delivery of production-ready models.

Location: LUX, Luxembourg

Company

Global leader in e-commerce, cloud computing, and artificial intelligence.

What you will do

• Lead and manage a team of Applied Scientists, Data Scientists, and Engineers, fostering innovation and scientific rigor.
• Define the science roadmap and prioritize classification initiatives across various compliance programs.
• Own end-to-end delivery of classification solutions, from problem framing and data strategy to model deployment.
• Drive architectural decisions regarding model selection, feature engineering, and evaluation metric frameworks.
• Collaborate with business teams to convert requirements into scalable ML solutions.
• Mentor team members through career coaching and structured growth plans.

Requirements

• Master's or PhD in Computer Science, Mathematics, Statistics, Machine Learning or a quantitative field.
• 8+ years of experience in data science or applied ML, with 3+ years in a people management role.
• Knowledge of LLM fundamentals, transformer architecture, and optimization techniques.
• Strong programming proficiency in Python and SQL, with familiarity with Spark and AWS services.
• Experience with multi-modal learning (text, image, structured data).
• Proven track record of delivering ML solutions at scale in production environments.

Nice to have

• Familiarity with compliance and regulatory classification frameworks (e.g., HS codes, hazmat classification, product safety).

Culture & Benefits

• Inclusive culture that empowers employees to deliver the best results for customers.
• Commitment to diversity and equal opportunity employment.
• Focus on innovation, simplifying processes, and building scalable systems.
• Environment emphasizing scientific rigor and operational excellence.