Sr. Fraud Specialist, RMO
San Jose , CR
hace 4 días


Overview : The Risk Mining Operations (RMO) Team is the Business Support team identifying the Risk Patterns in Buyer, Seller, & Payment spaces while working closely with the Analytics team to ensure seamless resolution to difficult & complex cases raised across from different businesses at Amazon.

RMO plays a critical role in reducing bad debt, providing operational insights into bad debt drivers through deep dives and investigations on system and manual misses.

Risk Mining Investigators are deeply knowledgeable of Seller, Buyer, Abuse, Payment platforms, tools and resources offering end to end resolution in identifying risks and ensuring the right controls are in place.

They work continuously with Stakeholders to build trust-based relationships in order to investigate Fraud cases and address escalations while creating long-term, systemic solutions for a world-class Customer experience.

RMO is seeking committed & results oriented candidates with a proven track record to join Buyer Risk Mining (BRM). Candidates will be responsible for a wide range of duties related to investigation and elimination of online e-commerce fraud.

The BRM position relies on analytical and critical thinking problem solving skills, including the ability to recommend solutions in an ambiguous & ever challenging environment.

Key Responsibilities :

1. Data Analysis & Conducting investigations into allegations of organized fraud or abuse on and off Amazon website.

2. Investigate suspicious orders, selling and buying behavior that could pose a risk to Amazon customers.

3. Use a combination of manual and automated tools to obtain information & report bugs and tool improvement ideas.

4. Take appropriate action to identify and help minimize the risk posed by fraud or abuse patterns and trends.

5. Consistently achieve / exceed weekly Targets and quality standards for investigations.

6. Deemed focus towards improving customer experience and contribute towards seller product team goals.

7. Participate in ad-hoc projects / assignments as necessary

8. Work Scheduled Shift - (8 : 30AM-5 : 30PM CST) with Sun / Mon or Fri / Sat week offs


  • A Bachelor’s degree
  • Strong, self-driven & motivated individual with demonstrated ability to perform well independently as part of a team.
  • A minimum of 4+ years' as a eCommerce fraud analyst or fraud investigator in risk and / or fraud
  • Proficient in data analysis in Microsoft Excel and more advanced programs such as SQL.
  • Experience with SAS, R or similar tools.
  • Excellent Communication (both written & verbal) & Leadership Skills
  • High Organizational, Time-Management and Decision Making Skills
  • Effective project management skills.
  • Strong business sense and ability to invent and innovate as part of a vision.
  • Ability to maintain high levels of confidentiality and data security
  • Demonstrated analytical and problem solving skills, including the ability to recognize non-obvious patterns

  • Bachelor’s Degree in any quantitative discipline such as Information Systems, Computer Science, Statistics, Operational Research or Engineering
  • Substantial experience working in Analytics / Business Intelligence environment
  • Experience in working with databases and SQL in a business environment
  • Demonstrated use of analytical packages and query languages such as SAS,SPSS and SQL
  • Prior experience in design and execution of analytical projects
  • Worked extensively in large scale data bases and data warehouses
  • Experience in e-commerce / on-line companies in fraud / risk control functions
  • Coding skills in one of the modern languages Java, Python, Scala, R
  • Experience with visualization technologies such as Tableau
  • Experience / knowledge of advanced machine learning techniques such as GBM, random forest, etc..
  • Compelling communication and influencing skills and participation in winning the support of management and influence the course of major strategic decisions.
  • Amazon is committed to a diverse and inclusive workplace.
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