Senior Applied Scientist , Buyer Risk Prevention (BRP)
Teknik, data och digitalt · Data, AI och analys · Datavetenskap · Maskininlärning
I korthet
Join Amazon's Buyer Risk Prevention team as a Senior Applied Scientist in Bengaluru. You will lead the development of large-scale machine learning systems to protect customers from fraud and risk, leveraging advanced technologies like Generative AI and LLMs. This role requires a PhD or Master's degree with 5+ years of applied research experience and strong programming skills.
Ansvarsområden
- Lead the end-to-end scientific strategy for large-scale fraud and risk modeling initiatives
- Define problem statements, success metrics, and long-term modeling roadmaps
- Design, develop, and deploy highly scalable machine learning systems in real-time production environments
- Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies
- Influence system architecture and partner with engineering teams
- Establish best practices for experimentation, model validation, monitoring, and lifecycle management
- Mentor and raise the technical bar for junior scientists
- Communicate complex scientific insights clearly to senior leadership and cross-functional stakeholders
- Identify emerging scientific trends and translate them into impactful production solutions
Krav
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 5+ 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
- Inclusive culture empowers Amazonians to deliver the best results for our customers.
- Workplace accommodations and adjustments are available for individuals with disabilities.
#machine learning#buyer risk prevention#fraud#risk management#Generative AI#LLMs