Applications are hereby welcomed from motivated data scientists with excellent leadership skills, and the ability to develop, automate, and run analytical models of systems.
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This opportunity at Amazon is highly competitive and is available to eligible candidates for internship currently enrolled in Master’s or Ph.D. degree in math, statistics, computer science, or related science field.
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What to Expect
Amazon is an equal opportunities employer. Believe passionately that employing a diverse workforce is central to success. The company makes recruiting decisions based on your experience and skills:
- 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.
Eligible Criteria
Applicants for AMAZON Data Science Internship Program are expected to meet the following criteria for this opportunity:
- Enrolled in Master’s or Ph.D. degree in math, statistics, computer science, or related science field.
- Experience with regression modeling, 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.
- Applicants have a demonstrated ability to manage medium-scale modeling projects, identify requirements, and build methodology and tools that are statistically grounded.
- You will have experience collaborating across organizational boundaries.
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How to Apply
If you are interested for AMAZON Data Science Internship Program, you are hereby advised that you must fulfill all the required criteria before you proceed to apply for this rare opportunity.
Begin your Registration
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- Drop comments for questions.
Support & Insights
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