Role at a glance
- Job function
-
Legal & Compliance Internal Audit & Investigations
- Salary
- Not Disclosed
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Education
- Bachelor's
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Qualifications
Required
- Bachelor's degree or equivalent
- Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets
- 5+ years of root cause analysis and process design experience
- Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership
- Experience in supply chain security, including management of third-party logistics providers, law enforcement, loss prevention, risk management, investigations or a similar field
Preferred
- Experience in data analytics or automation
- Familiarity with machine learning model evaluation metrics (precision, recall, F1, AUC) and experience providing feedback to science teams.
- Experience investigating organized fraud networks, supply chain fraud, counterfeit goods, or stolen goods.
About the role
Original posting provided by amazon
As part of TSI org, the Inventory Trust (IT) team is
responsible for detecting and preventing inventory from bad actors reaching our customers. We build proactive detection mechanisms, risk models, and intelligence-driven processes to identify bad actors before they impact customers.
We are looking for a Risk Manager who thrives at the intersection of data-driven detection and investigative deep dives. In this role, you will lead efforts to improve detection model accuracy, build rapid-response risk rulesets for emerging modus operandi (MOs), investigate bad actor networks end-to-end, and partner with science and engineering teams to close detection gaps. You will work across Supply Chain Risk Detection, ORC investigations, and external intelligence programs to ensure our mechanisms stay ahead of evolving bad actor tactics.
The ideal candidate is a strategic thinker with deep investigative experience, capable of building and scaling sophisticated detection programs to combat bad actor networks.
Key job responsibilities
Lead deep dives on detection model performance (precision, recall) to identify signal gaps, false positive/negative drivers, and improvement opportunities for existing risk models.
Develop recommendations for feature engineering, threshold tuning, and signal integration.
Own end-to-end root cause analysis on detection defects, false positives, reinstatements, and escalations to identify systemic gaps in detection logic
Analyze escalation patterns to identify detection blind spots and prioritize coverage expansion.
Build and deploy quick-turn risk detection rulesets and heuristics to address newly identified bad actor MOs, emerging fraud patterns, and intelligence leads before models can be retrained. Translate external intelligence (ORC referrals, brand leads, cargo theft data, stolen serial number matches, law enforcement tips) into actionable detection queries and monitoring rules.
Continuously monitor and refine detection rulesets based on hit rates, enforcement outcomes, and evolving bad actor tactics; sunset rules that lose effectiveness.
Perform full-sweep investigations on bad actor rings by casting wide nets from early leads, expanding from a single enforcement to identify connected sellers, shared suppliers, common locations, financial linkages, and secondary user patterns.
Basic Qualifications
- Bachelor's degree or equivalent- Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets
- 5+ years of root cause analysis and process design experience
- Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership
- Experience in supply chain security, including management of third-party logistics providers, law enforcement, loss prevention, risk management, investigations or a similar field
Preferred Qualifications
- Experience in data analytics or automation- Familiarity with machine learning model evaluation metrics (precision, recall, F1, AUC) and experience providing feedback to science teams.
- Experience investigating organized fraud networks, supply chain fraud, counterfeit goods, or stolen goods.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 121,200.00 - 163,900.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.