DESCRIPTION

Amazon Web Services (AWS) is building a world-class marketing organization, and we are looking for an experienced Applied Scientist to join the central data and science organization for AWS Marketing. You will lead AWS Measurement, targeting, recommendation, forecasting related AI/ML products and initiatives, and own mechanisms to raise the science and measurement standard. You will work with economists, scientists and engineers within the team, and partner with product and business teams across AWS Marketing to build the next generation marketing measurement, valuation and machine learning capabilities directly leading to improvements in our key performance metrics.

A successful candidate has an entrepreneurial spirit and wants to make a big impact on AWS growth. You will develop strong working relationships and thrive in a collaborative team environment. You will work closely with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services. The ideal candidate will have experience with machine learning models and causal inference. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.

You will work on high-impact, high-visibility products, with your work improving the experience of AWS leads and customers.


Key job responsibilities
- Lead the design, development, deployment, and innovation of advanced science models in the strategic area of marketing measurement and optimization.
- Partner with scientists, economists, engineers, and product leaders to break down complex business problems into science approaches.
- Understand and mine the large amount of data, prototype and implement new learning algorithms and prediction techniques to improve long-term causal estimation approaches.
- Design, build, and deploy effective and innovative ML solutions to improve components of our ML and causal inference pipelines.
- Influence long-term science initiatives and mentor other scientists across AWS.