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

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.


- 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
- Masters degree in a quantitative field such as statistics mathematics data science business analytics economics finance engineering or computer science
- Proven track record of end-to-end ML model delivery: problem formulation feature engineering training deployment monitoring
- Experience designing and analyzing A/B experiments at scale with rigorous statistical methodology
- Demonstrated ability to translate ambiguous business problems into well-scoped science deliverables
- Strong written and verbal communication ability to present complex findings to non-technical stakeholders
- Experience working with or evaluating AI systems

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

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