The Economic Technology team (EconTech, ET) is looking for an a experienced Applied Scientist Manager to build Reinforcement Learning solutions to solve economic problems at scale. ET uses Machine Learning, Reinforcement Learning, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business. We also develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Economists, Engineers, and Scientists incubating and building disruptive solutions using cutting-edge technology to solve some of the toughest business problems at Amazon.
You will lead multiple teams of engineers, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services. You will provide thought leadership to scientists, economists, and engineers to help invent and implement scalable ML, RL, and econometric models while building tools to help our customers gain and apply insights. This is a unique, high visibility opportunity for a leader who wants to have business impact, dive deep into large-scale economic problems, and enable measurable actions on the Consumer economy. We are particularly interested in candidates with experience building predictive models and working with distributed systems.
As a Manager, Applied Science, you bring structure to ambiguous business problems and use science, logic, and practical experience to decompose them into straightforward, scalable solutions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems; you're interested in learning; and you acquire skills and expertise as needed..
As an Applied Science Manager, you will:
· Lead a group of talented applied scientists and software engineers to deliver machine-learning and AI solutions to production.
· Advance team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.
· Develop science and engineering roadmap, run Sprint/quarter and annual planning, and foster cross-team collaboration to execute complex projects.
· Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.
· Hire and develop top talents, provide technical and career development guidance to both scientists and engineers in the organization.
· Ph.D in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, Statistics, Mathematics, or related discipline
· At least 2 years of experience in managing a team of Applied Scientists and Software Development Engineers.
· At least 2 years of experience in building large-scale machine learning and solutions at internet scale.
· At least 4 years of programming experience in Java, Python, Scala, C++, or other mainstream languages
· At least 2 years' of experience in Big Data technologies such as: AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza.
· Experience with Internet-scale distributed technologies and concepts such as large-scale recommendation, personalization, search, advertising, etc.
· Published research work in academic conferences or industry circles
· Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization
· Experience in computational advertising