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The Special Projects & Investigations team is looking for an experienced, motivated Scaled Abuse Specialist (formerly called Industry Specialist) with background in risk, digital fraud, compliance who also have advanced data analysis skills (SQL, Python, Machine Learning, Data Science). This role will manage critical and high impact projects and scale their findings through technology and analytics to interpret risks across Amazon's entire business segment or apply other industry experience to develop feasible, systematic solutions to endemic problems.
Selling Partner Trust and Store Integrity (TSI) creates a trustworthy shopping experience across Amazon stores worldwide by protecting customers, brands, selling partners, vendors, and Amazon from fraud, counterfeit, and abuse. The Special Projects and Investigations (SPI) team within TSI protects Amazon customers and stores by applying systems thinking to understand how networks of users interact with multiple services. We target large-scale ecosystems that pose store-level risks and mitigate those ecosystems through internal and external means. Our growth requires highly skilled candidates who move fast, have an entrepreneurial spirit to create new solutions, demonstrate tenacity to get things done, thrive in ambiguity and change, and can break down and solve complex problems.
We catch bad actors and stop online fraud. It's fun. It's hard. It matters. We are passionate about protecting our selling partners and customers from bad actors and want a candidate that shares that passion. Amazon is one of the world's most trusted companies. Help us keep it that way. To achieve this, the ideal candidate should be passionate about use of advanced data analytics and technology approaches to identify patterns and establish connections to uncover process and technology gaps and prevent fraud across Amazon stores worldwide. Your decisions are not only fundamental to helping protect customers and selling partners but will help maintain the health of Amazon's catalog and product listings ecosystem.
Key job responsibilities
• Complete risk analyses and manipulate data in complex data sets (SQL, Python, R etc.)
• Use high-level judgment to inform our most complex enforcement decisions
• Identify gaps and risks in Amazon's current mechanisms and policies and recommend solutions to product/policy owning teams.
• Use data and/or technical skills to discover new ways to scale deep dive signals resulting in the identification of many bad actors and sizing the issue
• Owning the complete life cycle of one or more complex problems - from identification through scaling the solutions
• Break problems into manageable pieces, ruthlessly prioritizing, and delivering results in an ambiguous environment
• Conduct large scale deep dives to derive insights about tactics used to conduct abuse on our stores, identifying gaps and risk in Amazon's current mechanisms, systems, and policies
• Write documents for partner teams and executives that identify problems, propose technical solutions, and drive alignment among stakeholders
• Own partnerships with stakeholder teams and guide appropriate trade-offs, clearly communicate goals, roles and responsibilities.
• Design and deploy agentic AI systems to automate complex workflows, scale pattern detection, and accelerate enforcement decisions across high-volume abuse scenarios
A day in the life
Your day might involve diving deep into data to uncover emerging fraud patterns, collaborating with teams across Amazon to implement protective solutions, or developing new detection methods. You'll balance independent analytical work with team collaboration, sharing insights and supporting colleagues in our shared mission.
About the team
Our team is comprised of practitioners of fraud and abuse, working to understand bad actor ecosystems using threat intelligence analytics and technical skills. We complement specialized industry skills with broad risk experiences gathered through years of experience to deliver results - we wear a lot of hats and take ownership of hard to solve problem areas whenever possible. We speak 12 languages, write code in 3 (mostly self-taught, on the job), and celebrate learning and taking risks. We encourage experimentation and curiosity while supporting each other to constantly learn and grow.
Our work is to solve hard puzzles and identify what hasn't already been discovered - typically with data and always with a lot persistence and curiosity. If you like the sound of that, come join us.
BASIC QUALIFICATIONS
- Bachelor's or postgraduate degree in Information Security, Computer Science, Data Science/Analytics, Engineering, Mathematics, Statistics or related discipline.
- 3+ years of relevant industry experience in risk or fraud investigations, regulatory compliance, ecommerce, analytics, or security
- Proficient with deriving insights from big data using SQL & experience manipulating/processing data with Python
- Proven ability to deliver complex projects across multiple teams
PREFERRED QUALIFICATIONS
- • Experience working in e-commerce organizations • Experience working within fraud, compliance, law enforcement, or intelligence organizations • Experience with AWS services like Redshift, Neptune or Sagemaker • Masters degree in or practical experience with data science or machine learning • Excellent written and verbal communication skills to communicate security and business risk to a broad range of technical and non-technical audiences. • High level of integrity and discretion to handle confidential information. • Exceptional ownership and bias for action: willing to move quickly and decisively • Proven ability to problem solve in large/complex/technical systems
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, AZ, Tempe - 102,000.00 - 178,400.00 USD annually
USA, WA, Seattle - 102,000.00 - 178,400.00 USD annually