2023 Data Science Internship

Job Description

Job summaryPlease note we may also have internship opportunities in Austria, France, Germany, Ireland, Luxembourg, Israel, Spain, Poland, ItalyAre you a MS or PhD student interested in a 2023 Internship in Data Science At Amazon, were working to be the most customer centric company on earth. To get there, we are looking for motivated and talented driven people.If youre insatiably curious and always want to learn more, then youve come to the right place. Depending on your location, country, job status and other requirements, some or all of the following benefits may be available to you as an intern.* Competitive pay* Impactful project and internship/role deliverables* Hybrid working (team dependent)* Networking opportunities with fellow interns * Internships events such as speaker series, intern panels, Leadership Principles sessions, Amazon writing skills sessions.* Mentorship and career developmentWe are looking for a customer obsessed Data Scientist Intern who can innovate in a business environment, building and deploying machine learning models to drive step-change innovation and scale it to EU/worldwide. If this describes you, come join our data scienceteams at Amazon for an exciting internship opportunity.If youre successful during your internship, you could be considered for a graduate role after finishing your university studiesInternship start dates vary throughout the year. Internship length can vary between 3 - 6 months for Full Time and 6 - 12 months for Part Time.Key job responsibilities* Work closely with scientists and engineers to architect and develop new algorithms to implement scientific solutions for Amazon problems.* Work on an interdisciplinary team on customer-obsessed research* Experience Amazons customer-focused culture* Create and Deliver Machine Learning projects that can be quickly applied starting locally and scaled to EU/worldwide* Build and deploy Machine Learning models using large data-sets and cloud technology.* Create and share with audiences of varying levels technical papers and presentations* Define metrics and design algorithms to estimate customer satisfaction and engagementBASIC QUALIFICATIONS * Enrolled in Masters or Ph.D. degree in math, statistics, computer science, or related science field. * Understanding of Machine Learning, Deep Learning, Forecasting, Experiments and Causal Inference* Proficiency in model development, model validation and model implementation* Experience with MySQL/PostgreSQL/Redshift* Proficiency with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)* Great design and problem-solving skills, passion for quality and engineering excellence at scalePREFERRED QUALIFICATIONS * Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data.* Experience implementing and deploying models at scale* Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive). * Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2.* Experience in communicating technically, at a level appropriate for the audience.Please note this is not a remote internship opportunity EU Student Programs TeamAmazon is an equal opportunities 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.Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need an adjustment during the application and hiring process, including support for the interview or onboarding process, please contact theApplicant-Candidate Accommodation Team (ACAT), Monday through Friday from 7:00 am GMT - 4:00 pm GMT. If calling directly from the United Kingdom, please dial + (tel:+). If calling from Ireland, please dial + (tel:+).