AmazonSr Risk Manager, Selling Partner Identity Verification
Amazon is hiring a Sr Risk Manager, Selling Partner Identity Verification in Seattle, United States. It pays $121k-$164k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Level rates this role Uses AI ●●○○: an ordinary role that requires AI tools.
- The posting mentions Python, Machine learning and risk management among its tools and skills.
- Level classes it as a senior role.
- Amazon has 21,000+ other open roles on Level.
AI in this role
Lead entity-level risk strategy by partnering with data science to build automated ML-driven detection logic and cross-account threat mitigation.
Amazon is seeking a highly analytical, strategic, and transformative Senior Risk Manager to lead our Entity Risk Strategy. This team is tasked with protecting Amazon's brand reputation, customer trust, and partner relationships by identifying, evaluating, and mitigating complex risks that transcend traditional platform boundaries.
In this role, you will own the overarching strategy to detect, assess, and resolve cross-account risks across Amazon's ecosystem, including Sellers, Buyers, Brands, Vendors, Amazon Pay (APay), and other account types. You will move beyond traditional siloed risk frameworks to establish a unified, entity-level risk assessment and governance structure. As a principal-level domain expert, you will build the scalable detection logic and resolution frameworks that connect disparate signals into a comprehensive defense, collaborating with senior leadership across Science, Engineering, Risk, Legal, Public Relations, and Global Operations to deploy global-scale mitigations against complex bad-actor networks.
Key job responsibilities
Unified Entity Strategy: Define and execute the multi-year strategy for a holistic, entity-level risk framework that maps and assesses threat surfaces across interconnected Seller, Buyer, Brand, Vendor, APay, and other account ecosystems.
Scalable Resolution Frameworks: Architect and enforce end-to-end policy, enforcement, and remediation frameworks that allow operational teams to execute precise, coordinated actions against related bad-actor networks.
Cross-Functional Stakeholder Alignment: Drive architectural alignment and policy consensus across specialized risk domains (e.g., Identity Risk, Financial Risk, Brand Protection, Payments Compliance) to ensure a unified defensive posture.
Data Automation and Architecture Integration: Partner with Data Science and Engineering teams to translate complex network insights and cross-account signals into automated feature engineering pipelines, graph structures, and machine learning models.
Governance and Executive Reporting: Maintain a comprehensive view of systemic cross-account vulnerabilities, authoring high-visibility executive whitepapers (Amazon 6-pagers) and presenting status metrics directly to VPs and Directors.
Basic qualifications
- Bachelor's degree or equivalent
- Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets
- Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership
- 5+ years of hands-on experience designing risk detection strategies specifically targetting cross-account relationships, seller, brand, vendor and other or complex multi-entity fraud networks.
- Experience developing risk coverage frameworks and detection logic that directly feed into automated mitigation engineering/Science pipelines.
Preferred qualifications
- Master's degree or equivalent
- Experience leading and influencing your team or organization, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Experience in data analytics or automation
- Technical familiarity with graph databases or network topology tools used to visualize multi-entity structures.
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
How we rate this
Sr Risk Manager, Selling Partner Identity Verification at Amazon rates 55 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where risk management was part of your work. What did you do?
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where feature engineering was part of your work. What did you do?
- Tell me about a project where fraud detection was part of your work. What did you do?
- Walk me through how you've used Python in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Risk Management, Data Science, Feature Engineering, Fraud Detection, and Python. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.
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