Buyer Risk Analysis Expert
11 hours ago
Become a critical member of Amazon's Account Integrity team, utilizing machine learning expertise to safeguard customer trust and security. This challenging role demands advanced problem-solving, effective communication, and strategic thinking to mitigate risks and optimize outcomes.
The Amazon Account Integrity team confronts the pressing issue of protecting customer trust without unfairly penalizing honest clients. By leveraging machine learning techniques, we develop sophisticated models to detect and address potential threats. This proactive approach enables us to refine our strategies continuously and respond promptly to emerging risks.
This position comes with a competitive salary range of $136,000-$222,200, influenced by geographic location. Your compensation package might include additional incentives, such as equity grants, signing bonuses, or other benefits. As an employee-friendly organization, Amazon provides a comprehensive set of health, financial, and other benefits to support your well-being.
Mandatory Qualifications:
- Postgraduate degree in Computer Science, Computer Engineering, or a related field (Master's or Doctorate) with a minimum of 4 years of professional experience
- Proven expertise in fields such as data analysis, algorithm design, and software development
- Strong proficiency in programming languages like Java, C++, or Python
- Crisp, concise communication and excellent presentation skills
Preferred Criteria:
- Ph.D. in Computer Science, Computer Engineering, or a related field
- A history of publishing in top-tier academic journals such as CVPR, ICCV, ECCV, or NeurIPS
- Significant experience in developing machine learning models or creating algorithms for business applications
- Demonstrated expertise in areas like deep learning, computer vision, human-robotic interaction, or algorithms
- Exceptional written, verbal, and data presentation abilities
We strive to create an inclusive work environment at Amazon and encourage talented individuals from diverse backgrounds to apply.
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