Sr Applied Scientist, Digital Ads , Amazon Digital Advertising

Amazon Amazon · Big Tech · Seattle, WA · Machine Learning Science

Senior Applied Scientist role focused on developing state-of-the-art measurement approaches and machine learning models for Amazon's digital advertising business, operating at Petabyte scale. The role involves designing and analyzing large-scale experiments, collaborating with engineering teams to productionize models, and establishing scalable processes for model development and validation. Requires expertise in experimental statistics, machine learning, or causal inference, with a focus on building sophisticated decision engines and measurement systems.

What you'd actually do

  1. Scientists at Amazon are expected to develop new techniques to process large data sets and contribute to design of automated systems.
  2. Apply ML, statistics or econometrics knowledge to develop and analyze prototype models.
  3. Design and analyze data from large-scale online experiments in order to validate prototype models
  4. Collaborate with scientists across teams in peer-review processes , publishing research in internal forms and industry conferences
  5. Partner closely with product and engineering teams to develop new measurement systems and translate prototype models to production.

Skills

Required

  • 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

Nice to have

  • 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.
  • Knowledge of causal inference

What the JD emphasized

  • Petabyte scale
  • latest machine learning methods
  • expert in experimental statistics, machine learning or causal inference
  • large data sets
  • causal inference background
  • building machine learning models for business application experience
  • neural deep learning methods and machine learning

Other signals

  • developing new state-of-the-art measurement approaches at Petabyte scale
  • leveraging our unique data, the latest machine learning methods and big data technologies
  • develop new systems and methods in the most challenging and data rich areas of marketing
  • expert in experimental statistics, machine learning or causal inference to design advanced new models with our world class data systems
  • partner with a dedicated engineering team measuring the impact Amazon's marketing and identifying opportunities for optimization at scale
  • move away from industry standard measurement systems and build sophisticated and insightful decision engines
  • integrate petabyte-scale distributed retail systems into a singular service to synthesize e-commerce data into measurement and optimization models
  • Scientists at Amazon are expected to develop new techniques to process large data sets and contribute to design of automated systems.
  • Apply ML, statistics or econometrics knowledge to develop and analyze prototype models.
  • Design and analyze data from large-scale online experiments in order to validate prototype models
  • Partner closely with product and engineering teams to develop new measurement systems and translate prototype models to production.
  • Establish scalable, efficient, and automated processes for large scale model development, validation, and implementation.
  • Research and experiment with novel statistical modeling approaches.