Business Analyst, Misleading Claims

Misleading Claims is part of the Regulatory Intelligence Safety and Compliance (RISC) organization. We are on a mission to protect customers from false and deceptive claims on products enabling trustworthy shopping experiences at Amazon.

We are seeking an experienced Business Analyst to drive the metrics strategy and data infrastructure for Amazons Misleading Claims program. This role will define build and own the key performance metrics that measure program effectiveness in protecting customers from deceptive product claims across our marketplace. The ideal candidate will independently identify underlying data sources design new metrics frameworks where none exist and deliver actionable insights that shape program direction. You will partner with Risk Management Tech Science and Ops teams to translate complex enforcement outcomes into measurable business indicators. Strong analytical judgment deep SQL proficiency and experience working with trust and safety or compliance programs are essential. This role requires the ability to operate independently in ambiguous fast-moving environments where data definitions and measurement approaches must be built from the ground up.

Key job responsibilities
The successful candidate will:

- Define and own the end-to-end metrics framework for the Misleading Claims program including identifying gaps in existing measurement creating new metrics and establishing baselines and targets for program performance
- Independently identify evaluate and onboard underlying data sources across enforcement detection and seller behavior systems to build a comprehensive data foundation for program analytics
- Design and build dashboards and reporting mechanisms that provide real-time visibility into program health enforcement accuracy detection coverage and seller impact
- Independently collaborate across cross-functional teams Risk Legal Operations Science Tech and Finance to align on metric definitions data requirements and reporting cadences
- Provide data-driven and actionable insights to senior stakeholders to influence roadmaps prioritize enforcement strategies and measure the effectiveness of ML/AI detection models
- Develop key performance indicators that track progress against business objectives including detection precision/recall false positive rates enforcement turnaround times and seller remediation outcomes
- Conduct deep-dive analyses on misleading claims trends abuse patterns and enforcement outcomes to identify root causes and recommend program improvements
- Build scalable repeatable analytical processes and self-service tools that reduce dependency on ad-hoc analysis and enable the team to make faster data-informed decisions

About the team
Misleading Claims is part of the Regulatory Intelligence Safety and Compliance (RISC) organization on a mission to protect customers from false and deceptive claims on products enabling trustworthy shopping experiences at Amazon. As a newly established enforcement program were building comprehensive policies designing enforcement mechanisms and developing scalable solutions leveraging ML/AI technologies to safeguard customers across our marketplace. Our team collaborates closely with Product Quality Legal Tech Science and Operations teams to define and execute misleading claims controls at scale. Were establishing success metrics creating seller education programs and implementing a risk-based approach that balances customer protection with seller success. This is an opportunity to shape a critical trust and safety program from the ground up with direct impact on customer experience and marketplace integrity.

- Bachelors degree or equivalent
- 2 years of business analyst data analyst or similar role experience
- Experience with data visualization using Tableau Quicksight or similar tools
- Experience with Excel
- Experience with SQL

- Experience defining requirements and using data and metrics to draw business insights
- Experience partnering with executive-level leaders to identifying and solving business issues

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