About the job
Have you ever wanted to solve a mystery or be part of solving a case? Are you fascinated by detective stories or crime shows on TV? Do you love to catch bad actors, build ML models and solve complex problems. If so, working on the WWOS Tech team as a Sr Applied Scientist is the place for you! We detect theft, fraud and organized crime happening across our global supply chain and operations for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the cost savings of Amazon's inventory losses.
Responsibilities
Own KPIs that measure theft/fraud management performance and efficiencies.
Detect and automate theft, fraud MOs
Detect organized crime rings and bad actor clusters
Perform end to end evaluation of operational defects, system gaps, and scaling challenges (both system and operational).
Contribute to the overall fraud management and product development strategies.
Present key learnings and vision to stakeholders and leadership.
Integrate ML detection models via software applications
Qualifications
Minimum
PhD in (Research, Statistics, Engineering, and Supply Chain); history of building fraud detections; detecting organized crime; ability to use data and research to make changes
Preferred
Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in ( Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of building fraud detections, detecting organized crime and the ability to use data and research to make changes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment.