Risk Manager II, Financial Fraud

Amazon is hiring a Risk Manager II, Financial Fraud in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Little AI ●○○○ is how Level rates this role: aI is not part of the work.
The posting mentions risk management, data analysis and fraud detection among its tools and skills.
Level classes it as a mid-level role.
Amazon has 21,000+ other open roles on Level.

AI in this role

Conducting complex fraud investigations and designing risk mitigation solutions in partnership with machine learning teams.

risk-managementdata-analysisfraud-detectionstakeholder-management

The Financial Fraud team's vision is to protect customers and Amazon financials from exposure to bad actors, thus disincentivizing and reducing their attempts to operate in our stores.

We are looking for a highly motivated risk manager to solve exciting business problems in large scale. This role will perform comprehensive investigations to identify business problems and root cause, use data to locate patterns of risks, and drive the implementation of large scale solutions. The risk manager will work with product and program managers, machine learning scientists, risk SMEs across areas, as well as external stakeholders.

As a Risk Manager, you will define end-to-end risk strategy, scope ambiguous problems, and design solutions in partnership with ML, engineering, and business teams. The role demands strong data analysis skills, the ability to drive prioritization and alignment across stakeholders, comfort operating in ambiguity, and the influence to move leaders across organizations and levels.

Key job responsibilities
- Conduct complex investigations and make high--judgment enforcement decisions in ambiguous, fast-paced environments
- Analyze large datasets to identify abuse patterns, anomalies, and emerging risks at scale
- Author deep-dive documents and propose scalable solutions to product, policy, and leadership stakeholders
- Contribute to strategic vision and communicate goals, roadmaps, and policy changes through BRDs, WBRs/MBRs/QBRs
- Influence without authority across product, tech, policy, legal, and finance teams to drive consensus and deliver results
- Drive efficiency through automation, eliminating non-value-add processes, and building mechanisms that scale in resource-constrained environments
- Operate independently—prioritizing multiple high-visibility initiatives, managing escalations, and making data-driven tradeoffs to maintain strategic deliverables

About the team
The Financial Fraud team manages risk vectors where bad actors seek financial gains through illegitimate activities on Amazon and cause negative impact to Amazon buyers. We monitor customer orders and financial risk throughout the seller journey, apply surgical treatments and enforcement actions to prevent bad actors from exploiting Amazon systems and processes, particularly during a customer order’s lifecycle, to protect customer experience and prevent financial loss. We strive to prevent bad actor impact to Amazon and its customers while minimizing unnecessary friction to selling partners.

Basic qualifications

- 4+ years of compliance program management, legal, governance, audit, risk/loss prevention, or equivalent experience
- Bachelor's degree or equivalent
- Experience handling confidential information
- Demonstrated experience conducting complex investigations using multiple data sources, leveraging data to propose solutions, and particularly with SQL and excel
- Experience owning risk mitigation strategy, end to end delivery, and communicating results to senior leadership
- Ability to work with incomplete information and make sound judgments under ambiguity

Preferred qualifications

- 3+ years of program requirements definition and data and metrics leveraging to drive improvements experience
- 5+ years of experience in investigative roles (fraud, abuse, risk intelligence, law enforcement analysis, or similar)
- Experience sourcing and analyzing data, including running, and modifying SQL queries to investigate anomalies and drive insights

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.

How we rate this

Risk Manager II, Financial Fraud at Amazon rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● 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.

Key facts

Risk Manager II, Financial Fraud is an open job at Amazon.
Level rates this role AI Level 1 of 4: Little AI.
The role is based in IN, KA, Bengaluru.
The job was posted on August 11, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Risk ManagementData AnalysisFraud DetectionStakeholder Management

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 analysis 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?
Tell me about a project where stakeholder management was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Risk Management, Data Analysis, Fraud Detection, and Stakeholder Management. 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.

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