AmazonPosted 1mo ago

Sr Data Scientist, Seller Economics, WW Global Selling - PMO

Sr Data Scientist, Seller Economics, WW Global Selling - PMO at Amazon scores 86 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

CN, 31, Shanghaimidfull-time

AI in this role

Amazon WW Global Selling is looking for a dynamic, highly motivated Sr Data Scientist to join the central PMO team. This is an unique opportunity to:

Play a highly visible role in an exciting and fast paced business
Drive high impact products and initiatives to continuously improve Sellers' experience, growth and profitability
Innovate with advanced seller insights and influence cross-functional and global partners for great ideas and products.
Influence and drive decisions of senior leadership

This role is well-suited for someone with a strong economics or causal ML foundation who wants to apply rigorous statistical thinking to real product decisions at scale. You'll need to be comfortable writing SQL, working with imperfect data, and partnering with stakeholders to turn analysis into product impact. The ideal candidate will be strong at performing deep dives to derive insights on Seller behaviors, identify key pain points and needs from Seller perspective, and keen on AI-powered innovations, including:

1. Science-backed segmentation with a self-iterating feedback loop: Clustering algorithms (k-means, hierarchical, DBSCAN), Feature engineering from catalog and sales data, Feedback-loop model design, Ability to explain model logic to non-technical stakeholders
2. Econometric model to identify high expansion intent sellers: Propensity scoring and intent modeling (logistic regression, gradient boosting, neural), Behavioral sequence modeling, Feature engineering from sparse event-driven data, Classification threshold calibration
3. Post-Enrollment Outcome Models: Causal inference and treatment effect estimation (DiD, PSM, synthetic control, IV), A/B test design, Reinforcement learning
Science-backed graduation signals framework: Time series modeling and threshold detection, Survival analysis or time-to-event modeling, Bayesian updating for threshold calibration, Real-time or near-real-time scoring pipeline design
4. Familiarity with GenAI and LLM frameworks; experience embedding science models into AI-powered products or agents

Key job responsibilities
Key job responsibilities
- Use advanced statistical and machine learning techniques to extract insights from complex, large-scale data sets
- Partner with business/product stakeholders and senior science peers to identify strategic data-driven opportunities to improve the seller experience with a focus on seller economics domain
- Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders
- Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization
- Design and implement end-to-end data science workflows, from data acquisition and cleaning to model development, testing, and deployment
- Support scalable, self-service data analyses by building datasets for analytics, reporting and ML use cases

About the team
We are WW Global Selling PMO team. We collaborate with WWGS business teams to identify key Seller needs and partner with global product teams to develop tools and solutions to improve Seller experience and sustainable growth.

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
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression

Preferred qualifications

- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team

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