Amazon PXTCS uses economics, behavioral science, statistics, and machine learning to identify products, mechanisms, and process improvements that enhance Amazonians' well-being and their ability to deliver value for Amazon's customers. The job is to spearhead science design and technical implementation innovations across predictive modeling and forecasting work-streams, enhancing existing models and creating new ones to empower leaders throughout Amazon to make data-driven business decisions.
Requirements
- 5+ years of building machine learning models for business application 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 distributed systems such as Hadoop, Spark etc.
Responsibilities
- Spearhead science design and technical implementation innovations across our predictive modeling and forecasting work-streams.
- Enhance existing models and create new ones, empowering leaders throughout Amazon to make data-driven business decisions.
- Collaborate with scientists and engineers to deliver solutions.
- Develop end-to-end ML solutions from problem formulation to deployment, maintaining high scientific standards and technical excellence throughout the process.
- Contribute to the team's science strategy, keeping pace with emerging AI/ML trends.
- Mentor junior scientists, fostering their growth by identifying high-impact opportunities.
- Provide guidance across different analysis levels and modeling approaches, enabling stakeholders to make informed, strategic decisions.
Other
- PhD, or Master's degree and 5+ years of applied research experience
- Leverage expertise in translating innovative science into impactful products to improve the lives and work of over a million people worldwide.
- Collaborate with HR teams across Amazon to make Amazon PXT the most scientific human resources organization in the world.
- Work closely with business stakeholders to address their specific needs.
- Excel at building advanced scientific solutions and are passionate about developing technologies that drive organizational change in the AI era.
