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Amazon Fall Data Science Internship - United States PhD Masters Student 
United States, Washington, Seattle 
76828900

10.06.2024
DESCRIPTION

Do you have a passion for data? Are you matriculating in a Master’s or PhD program? Amazon is looking for driven data science students with strong modeling skills who are comfortable owning and executing data. To be successful in this internship, you will need the ability to develop, automate, and run analytical models for our systems. During this internship, you will build tools and support structures needed to analyze and dive deep into data to resolve systems errors and changes. You will have the ability to present your findings to our business partners and help drive improvements.Previous applicants demonstrated the aptitude to manage medium-scale modeling projects, identified requirements, and built methodology/tools that were statistically grounded.

BASIC QUALIFICATIONS

· Enrolled in a Master's degree or equivalent in math, statistics, computer science, or related science field.
· Experience with regression modeling, prediction, forecasting, and time series analysis.
· Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· Experience using one or more programming languages (e.g., Python, Java, C++, C, etc.).
· Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data.


PREFERRED QUALIFICATIONS

· Enrolled in a Ph.D. degree or equivalent in math, statistics, computer science, or related science field.
· Experience in machine-learning methodologies (e.g., supervised and unsupervised learning, deep learning, etc.)
· Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive).
· Experience in communicating technically, at a level appropriate for the audience.Pursuant to the Los Angeles and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.