Data Scientist, Retail Machine Learning Bardi

Data Scientist, Retail Machine Learning
Bardi
Emilia Romagna, Bardi

DESCRIPTIONAt Amazon, we're working to be the most customer centric company on earth.

To get there, we need exceptionally talented, bright, and driven people.

We are looking for a customer obsessed Data Scientist who can innovate in a business environment, building and deploying machine learning models. Our teams goal is to drive step-change innovation in both Customer Experience and Business management, by creating and delivering Machine Learning projects that can be quickly applied starting in Italy and Spain, and scaled to EU/worldwide.

We work on substantial problems that require to gather intelligence through data, and to build solutions that step-change the way in which we manage our Retail business. As a Data Scientist on our team, you will have opportunities to build and deploy Machine Learning models using large data-sets and cloud technology.

You will identify specific and actionable opportunities to solve existing business problems, and collaborate with technical andbusiness teams for future innovation.

You need to be a sophisticated user of advanced Machine Learning algorithms, cloud technology for model production, results delivery and visualization, and an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. The role will be based in Milan. BASIC QUALIFICATIONSMasters in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent). Great design and problem-solving skills, passion for quality and engineering excellence at scale. 5+ years of working experienceHands-on experience in building Machine Learning models and in Python language using ML libraries (scikit-learn, keras)Experience with AWS technologies such as Amazon SageMaker, Lambda, Redshift, S3, EC2, Data Pipeline, EMRWork well in a fast-moving team environment and effectively deliver technical implementations having complex dependenciesExemplary communication skills, ability to work with large cross functional teams of technical and non-technical membersAbility to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectivesAbility to manage and quantify improvement in customer experience or value for the business resulting from research outcomesPREFERRED QUALIFICATIONSExpertise in specialized areas such as Natural Language Processing, Fraud Detection and Time Series ForecastingExpertise in building model pipeline on AWS and writing production level codeStrong interest in learning, researching, and creating new technologies with high commercial impact