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

Overview

Team & Project OverviewThe 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 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 sell

What you'll do

• Team & Project OverviewThe 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 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.

Requirements

• Practical experience with React, Python, Go, LLM.
• Experience level: 5+ yrs.
• Strong written and verbal communication in English.
• Comfortable working on-site in Shanghai, CHN.

Skills