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Senior Data Scientist, AI Program, CNGS NBS (New Business & New Seller) Amazon Business

Amazon

Senior Data Scientist, AI Program, CNGS NBS (New Business & New Seller) Amazon Business

full-timePosted: Aug 17, 2026Updated: Aug 27, 2026Shanghai, 31, People's Republic of China

Job Description

Team & Project Overview The NBS Data Central team powers analytics, data science, and AI capabilities for Worldwide Global Selling (WWGS). We build scalable data products, and insight-generation systems that drive seller growth across 10+ marketplaces. Seller Intelligence is a P0 foundation theme at the Global Selling level, formed by merging "One Tagging" and "Good Contact" workstreams. It provides seller identity, segmentation, and contact-reach infrastructure that underpins all downstream seller-facing AI workflows — including intelligent outreach, personalized recommendations, and automated engagement. Scope of Impact Own the science pillar for Seller Intelligence within a cross-functional POD (PM + DE + DS + SDE) Directly impact seller engagement metrics across CN, IN, LATAM, and East-Asia expansion regions Models and data products consumed by 5+ downstream teams (ESM, NSR, MKT, NBS AI Ops, ROC) Influence $100M+ annual seller GMS through improved segmentation and contact optimization Key job responsibilities Design and deliver seller segmentation and propensity models at scale — incorporating GMS, category, growth trajectory, engagement signals, and lifecycle stage. Build contact quality scoring and lifecycle management systems (coverage optimization, dormancy detection, reactivation modeling). Define success metrics, experimentation frameworks (A/B, causal inference), and measurement methodology for seller engagement interventions. Productionize ML models and data products — partner with engineering to deploy seller scores, contact quality indices, and recommendation signals. Explore LLM/GenAI applications: automated insight generation from seller data, contact intent classification, and intelligent report synthesis. Serve as the science representative in bi-weekly NBS theme reviews; present findings and proposals to theme Bar Raisers and leadership. Collaborate with BIE team members to democratize analytical outputs via dashboards and self-serve tools. Contribute to cross-marketplace seller behavior analysis supporting Global Expansion strategy (IN, KR, VN, LATAM). Evaluate, integrate, and iterate on AI systems — assess new AI/ML tools, frameworks, and third-party models for applicability to seller intelligence use cases.

Locations

  • Shanghai, 31, People's Republic of China

Skills Required

  • NLP/LLM applicationsintermediate
  • seller/customer segmentationintermediate
  • distributed computing frameworksintermediate
  • causal inference methodsintermediate
  • knowledge graph constructionintermediate

Required Qualifications

  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience (experience, 5 years)
  • Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science (degree in a quantitative field such as statistics)
  • Proven track record of end-to-end ML model delivery: problem formulation → feature engineering → training → deployment → monitoring (experience)
  • Experience designing and analyzing A/B experiments at scale with rigorous statistical methodology (experience)
  • Demonstrated ability to translate ambiguous business problems into well-scoped science deliverables (experience)
  • Strong written and verbal communication — ability to present complex findings to non-technical stakeholders (experience)
  • Experience working with or evaluating AI systems (experience)

Preferred Qualifications

  • Ph.D. in a quantitative field (Statistics, Machine Learning, Economics, Operations Research) (experience)
  • Experience with NLP/LLM applications (text classification, intent detection, embedding-based retrieval, RAG pipelines) (experience)
  • Experience in seller/customer segmentation, propensity modeling, or CRM/lifecycle analytics (experience)
  • Proficiency with distributed computing frameworks (Spark, EMR, Redshift, Hive) (experience)
  • Experience working in a marketplace or platform business (e-commerce, SaaS, fintech) (experience)
  • Familiarity with causal inference methods (DID, RDD, synthetic control, instrumental variables) (experience)
  • Experience mentoring junior data scientists or leading a small science team (experience)
  • Track record of publishing research papers or creating reusable analytical frameworks (experience)
  • Knowledge of knowledge graph construction, entity resolution, or identity systems (experience)

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