Sr. Applied Scientist, WWOS Tech
Teknik, data och digitalt · Data, AI och analys · Datavetenskap · Maskininlärning · Artificiell intelligens
I korthet
Sr. Applied Scientist position focused on detecting theft, fraud, and organized crime within Amazon's global supply chain. The role involves building ML models, analyzing operational data, and influencing strategic decisions to minimize inventory losses and improve customer experience. Requires a PhD or Master's degree with applied research experience and strong programming skills.
Ansvarsområden
- 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.
- 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.
Krav
- 3+ years of building machine learning models for business application experience.
- PhD, or Master's degree and 6+ years of applied research experience.
- Experience programming in Java, C++, Python or related language.
- Experience with neural deep learning methods and machine learning.
Önskade kvalifikationer
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
Förmåner
- Foster new game-changing ideas.
- Create ever more intelligent and self-learning systems.
- Maximize cost savings of Amazon's inventory losses.
- Responsibility on day one to own business challenges.
- Autonomy to think strategically and make data-driven decisions.
- Significant impact on customer experience and fraud investigations.
- Work with a team but also comfortable making decisions independently.
- Inclusive culture empowering Amazonians.
- High value on work-life balance.
- Support for people with disabilities during the application and hiring process.
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