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

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.

Basic 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
• Master's 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

Preferred Qualifications

• 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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