Passionate about Deep Learning, Causal Inference, and Big Data Systems? Interested in building new state-of-the-art measurement products at petabyte scale? Be part of a team of industry leading experts that operates one of the largest big data and machine learning stacks at Amazon. Amazon is leveraging its highly unique data and applying the latest machine learning and big data technologies to change the way marketers optimize their advertising spend. Our campaign measurement and reporting systems apply these technologies on many billions of events in near real time.
In this role you will lead a team of scientists to tackle some of the hardest problems in advertising; measuring ads incrementality, providing estimated counterfactuals and predicting the success of advertising strategies. You and your team will develop state of the art causal learning, deep learning, and predictive techniques to help marketers understand and optimize their spend. As the primary leader for the Measurement Science team you will be partnering with VPs and Directors across all of our Ads verticals, driving growth and innovation.
Some things you'll do in this role:
· Work closely with scientists and engineers to architect and develop the best technical design and approach.
· Be a hands-on technical leader and player-coach; inspire and empower innovation and thinking big in those around you.
· Hire and develop a high performing team of scientists, raising the bar with each hire and mentoring your team to attain their business and career goals
· Develop and execute project plans and delivery commitments; manage the day-to-day activities of the science team
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
· MSc or PhD in Computer Science (Machine Learning, AI), Econometrics, Statistics, or equivalent;
· 15+ years of practical experience applying ML to solve complex problems for large-scale applications;
· 8+ years of experience managing one or more machine learning teams, with a strong track record of hiring and leading scientists;
· At least 5 years of experience with a language used in scientific programming such as Java, Python, or Scala
· PhD in Computer Science (Machine Learning, AI), Econometrics, Statistics, or equivalent;
· Experience in deep learning, causal learning, or bandit learning
· Experience in data applications using large scale distributed systems (e.g. EMR, Spark, Elasticsearch, Hadoop, Pig, Hive)
· Track record of peer-reviewed scientific publications
· Previously held a technical leadership role for several complete large-scale initiatives