Senior Applied Scientist
3 days ago
We are seeking a highly skilled Senior Applied Scientist to join our Enterprise Engineering team at Amazon. As a key member of our applied science team, you will leverage cutting-edge machine learning, natural language processing, and data analytics techniques to solve complex challenges in software discovery, cost optimization, and intelligent decision-making.
Key Responsibilities- Design, implement, and deliver scientifically complex solutions for software asset management, focusing on areas such as automated software discovery, intelligent cost optimization, and predictive analytics.
- Develop and apply state-of-the-art machine learning models to improve software categorization, usage prediction, and anomaly detection.
- Create innovative natural language processing solutions for contract analysis, optimization, and automated report generation.
- Design and implement advanced recommendation systems for software stack optimization based on job roles and team compositions.
- Develop reinforcement learning algorithms for automated license management, including predictive maintenance to prevent unexpected expirations or overage charges.
- Develop AI-driven negotiation assistants and collaborative budgeting tools with ML-powered spend forecasting.
- Create sentiment analysis models to gauge software satisfaction from user feedback and support tickets.
The AppSense team is at the forefront of transforming software asset management at Amazon. We're building a comprehensive platform that provides visibility, control, and optimization for Amazon's vast software portfolio. Our mission is to leverage cutting-edge technology to help businesses discover, manage, and optimize their software assets, driving significant cost savings and operational efficiencies.
Requirements- 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.
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability.
- Experience using managed ML/AI solutions.
- Strong skills in problem solving, programming, and computer science fundamentals.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
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