This role is available across multiple locations (United Kingdom, Germany, Luxembourg, Italy, Spain and France). Amazon Internships have start dates throughout the year and can vary in length from 3-6 months for full-time. Please note these are not remote internships.
Are you a MS or PhD student interested in a 2024 Internship in Data Science? We 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 the EU/worldwide. If this describes you, come and join our Data Science teams at Amazon for an exciting internship opportunity. If you are insatiably curious and always want to learn more, then you’ve come to the right place.
Key job responsibilities
As a Data Science Intern, you will have following 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 Amazon's 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 engagement
For more information on the Amazon Science community please visit the Science hub page: https://www.amazon.science/
For more information on the Amazon Science internship program in EMEA please visit this page: https://amazonscienceopportunitiesemea.splashthat.com/
We are open to hiring candidates to work out of one of the following locations:
* Enrolled in Master’s 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 scale
* 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
* Amazon values knowledge of Accessibility in relation to its products, devices, services, websites or environments, so as to be usable by people with disabilities
* Previous corporate work experience is not required
Amazon 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://www.amazon.jobs/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 the Applicant-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 +44 800 086 9884 (tel:+448000869884). If calling from Ireland, please dial +353 1800 851 489 (tel:+3531800851489).