Amazon.com Services LLC
Machine Learning Science, Applied Science, Advertising
SrAppliedScientist,DigitalAds
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“Sr Applied Scientist, Digital Ads at Amazon.com Services LLC. Skills: Machine learning, Causal inference, Data science, Applied science. Develop new techniques to process large data sets. Contribute to design of automated systems”
What You'll Achieve.
Improve relevance of advertising to customers; Make smarter marketing decisions
Industry & Context.
Solving problems with large data sets; Identify opportunities for optimization
What They're Looking For.
Must Have
4+ years building ML models, PhD or Master's degree, 6+ years applied research experience, Experience programming in Java, C++, Python, Experience with neural deep learning methods, Experience with machine learning, Causal inference background
Nice to Have
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Experience with large scale distributed systems such as Hadoop, Spark, PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
Develop new techniques to process large data sets
Contribute to design of automated systems
statistics or econometrics knowledge
Develop prototype models
Analyze prototype models
Design data from large-scale online experiments
Analyze data from large-scale online experiments
Validate prototype models
Collaborate with scientists across teams
Publish research in internal forms
Publish research in industry conferences
Partner closely with product teams
Partner closely with engineering teams
Develop new measurement systems
Translate prototype models to production
Establish scalable processes
Establish efficient processes
Establish automated processes for model development
Establish automated processes for model validation
Establish automated processes for model implementation
Research novel statistical modeling approaches
Experiment with novel statistical modeling approaches
How You'll Work.
Team & Collaboration
Scientists across teams; Product teams; Engineering teams
Communication Scope
Publishing research
Full Job Description
Are you passionate about developing new state-of-the-art measurement approaches at Petabyte scale? Amazon Advertising is one of Amazon’s fastest growing businesses, and we are leveraging our unique data, the latest machine learning methods and big data technologies to better understand how Amazon’s marketing influences customer behavior. We are looking for a Senior Applied Scientist to develop new systems and methods in the most challenging and data rich areas of marketing. We need an expert in experimental statistics, machine learning or causal inference to design advanced new models with our world class data systems. Dozens of Amazon businesses use Amazon’s ad tech for their marketing objectives, driving more than $1B of marketing investments through Ads services and tools. As part of the 1PM team, this role will partner with a dedicated engineering team measuring the impact Amazon's marketing and identifying opportunities for optimization at scale. We drive initiatives to make smarter marketing decisions and improve the relevance of advertising to our customers. We move away from industry standard measurement systems and build sophisticated and insightful decision engines. We enable massive advertising programs, generating billions of impressions decorated with rich representations of customer state. The major challenges we are solving include integrating petabyte-scale distributed retail systems into a singular service to synthesize e-commerce data into measurement and optimization models. The successful candidate will have a causal inference background, a start-up mentality, an appreciation for white-space, and success solving problems with large data sets. Key job responsibilities • 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 experime
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