Amazon is looking for a Data Scientist with a passion for languages to join our Alexa AI - Natural Understanding Turin team. We are seeking a candidate with strong analytical skills and Natural Language Processing (NLP) experience to help us develop language components for a variety of Alexa products. Come join the Alexa team, building the speech and language solutions behind Alexa, Amazon Echo and other Amazon products and services! You will help us invent the future. As a NLP Data Scientist of the Alexa AI - NU Team, you will work close with Language Engineers to build and releases NLU models in production and improve them. You will gain hands-on experience with Amazon’s heterogeneous structured data sources; as well as large-scale computing resources to accelerate advances in training deep neural networks for natural language understanding. You will take lead on solving highly visible and impactful business problems in areas of automation, self-service solution and quality improvement to continue delight Alexa customers and help driving Amazon business performance. The ideal candidate is clearly passionate about delivering experiences that delight customers and creating solutions that are robust. Creating reliable, scalable and high performance products requires exceptional technical expertise, and a sound understanding of the fundamentals of Machine Learning, NLP, Linguistic and Problem solving. This role requires working closely with business, engineering and other scientists within the team and across Amazon to raise the bar in operational excellence, improving tools and automating workflows. You will lead high visibility and high impact programs collaborating with various teams across Amazon. You will focus on deliver results with the right quality and in a timely fashion. Your bias for action will be critical to move quickly on projects, with calculated risk taking.
QUALIFICHE DI BASE
· A Bachelor’s degree in Statistics / Applied Mathematics / Operation Research / Engineering / Data Science or other related quantitative fields.
· 5+ years (practical) experience in one of these fields: NLP, ML, computational linguistics, language data processing, software development
· Proficiency in scripting, querying and/or analytics tools, such as Python, R, SQL or similar.
· Ability to program to solve problems and automate repetitive tasks in a common scripting or programming language such as Python, with understanding of the UNIX/Linux operating systems
· Proficient with various machine learning techniques, and understands factors that affect their performance.
· Proved experience with Python (focus on PyTorch, TensorFlow, MxNet or similar frameworks);
· Experience with R or other statistical / machine learning focused programming language;
· Experience using SQL to extract and process large data-sets in a business environment;
· Proved contributions to Natural Language Processing projects;
· Fluency in written and spoken English (CEFR B2) and reading Spanish (B1) language;
· Knowledge of a number (but not all) of the following topics: Design of experiments, Formulating the biz problem-modeling, Feature selection & feature engineering, Supervised, semi-supervised, and unsupervised models, Statistical testing (chi square, t test for differences), Generalized linear/additive models, Mixed models, Random forest, Clustering techniques, DNN & hyperparameter optimization, Bayesian approaches, Bootstrap/boosting, Cross-validation and model performance evaluation, Practical knowledge of version control and agile development.
· A Master’s degree or PhD in Statistics / Applied Mathematics / Operation Research / Engineering / Data Science or other related quantitative fields.
· PhD in Computational Linguistics, or a related field
· Strong background in deep learning, recommender systems, or reinforcement learning.
· Experience with software engineering, or deploying machine learning models to production.
· Experience in designing, launching, and analyzing A/B tests to measure business impact.
· Experience with machine learning applications for voice-powered devices or marketing.
· Track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
· Experience with writing academic styled papers for presenting both the methods used and results for data science projects.
· Prior work experience on a multidisciplinary team of scientists and engineers
Amazon is an equal opportunity employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.