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[2020-08-01]   Sr Data Scientist
Jobbeschreibung
Masters in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)5+ years of experience working in data science in a consumer product company, managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or EconomistsExperience in hiring and leading experienced scientists as well as a successful record of developing junior members to a successful career trackUnderstands challenges in business area, applicability of relevant data science disciplines, and system interactions; able to keep others current on scientific advancementsExperience with math/stats software, i.e. R, Python or other domain specific softwareStrong communicator, able to communicate goals and strategies across multiple leadership levels of an organizationPragmatic problem solver, applying judgment and experience to balance cross-organization trade-offs between competing interestsFlexible, adapting your approach to meet the needs of the team, project, and productTeam player who works constructively and transparently within the wider teamStrong sense of urgency and personal commitment
Amazon's Customer Service (CS) department is seeking an experienced Data Scientist to join the team. Customer service is the heart of Amazon, our vision is to be "Earth's most customer centric company; to build a place where people can come to find and discover anything they might want to buy online."
The successful candidate will be a key member of the EU Customer Service Data and Insights team. The mission of this new team will be to analyse customer feedback, create actionable insights and improve the customer experience together with our EU business partners.
As the leading EU CS Data Scientist, you will own the analytical strategy for EU Customer Service. As a “hands-on” data science leader, you lead large projects to drive customer experience improvements, often in new territory, with quantifiable impact for the customer. You drive experiments and rigorous analysis to innovatively answer business questions and evaluate our service. You are able to develop solutions for highly complex business problems that may extend into other organizations. You anticipate and develop solutions that can address forward-looking business problems. You simplify the design and improve the accuracy of existing solutions, models, processes, and technologies.

This position can be located in any EU CS ((Cork, Edinburgh, Regensburg, Berlin, Rabat, Cagliari) or corporate site (London, Paris, Madrid, Milan, Paris, Luxembourg).

*This role requires a valid visa/work permit*

Key Responsibilities:
Responsibility includes but is not limited to:
Define the analytical strategy and build a roadmap to support EU Customer Service strategy and customer effort reductionInfluence EU CS strategy and business partners by challenging assumptions and driving evidence-based decision makingEvaluate cross-team perspectives and understand how interactions among teams, processes, and software systems need to be modeled in analytics solutionsInvestigate the feasibility of applying scientific principles and concepts to business problems and productsDeep dive into a significant opportunity, designing the right scientific approach and delivering the solution to drive data insight or describe an end-to-end systemDevelop scalable algorithms and models to support business decision makingHelp raise awareness and educate the organization on new and well-established data science techniques
French, German, Italian or Spanish language skills would be advantageous but is not essentialA PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval, XGBoost, LightGBM, ElasticNet.Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker.Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval

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