Data Scientist Intern
- Must be enrolled at a university and plan to return for additional school terms prior to graduating. Otherwise, please apply to the Data Scientist full-time posting if you are graduating prior to August 2018.*
Are you passionate about applying your strong quantitative analysis and big data skills to world-changing problems? Are you interested in driving the development of methods, models and systems for state-of-the-art robotics, transportation and fulfillment systems? If so, then this is the job for you.
We are looking for motivated students with excellent leadership skills, and the ability to develop, automate, and run analytical models of our systems. Applicants will have strong modeling skills and is comfortable owning their own data and working from concept through to execution. This role will also build tools and support structures needed to analyze data, dive deep into data to resolve root causes of systems errors & changes, and present findings to business partners to drive improvements.
Applicants must have a demonstrated ability to run medium-scale modeling projects, identify requirements and build methodology and tools that are statistically grounded. You will have experience collaborating across organizational boundaries.
Internships last 12-20 weeks and start year round. In order to be considered for an internship you must be enrolled at a university and plan to return for additional school terms prior to graduating. Otherwise, please apply to the Data Scientist full-time posting if you are graduating within the next year.
- In the process of obtaining an advanced degree (Ph.D. strongly preferred) in Engineering, Math, Statistics, Finance, Computer Science, or related industry experience
- 1+ year experience with statistical tools (e.g. R) and analysis, regression modeling and forecasting, time series analysis. Able to write SQL scripts for analysis and reporting ( SQL, MySQL)
- Experience using one or more programming languages (e.g. Python, Java, C++, C#, Ruby)
- Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data
- Preferred graduation date between August 2018 and July 2019
- 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, Hive)
- Experience in communicating technically, at a level appropriate for the audience
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