Data Scientist Graduate Intern

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Responsibilities may be quite diverse of a nonexempt technical nature.

• U.S. experience and education requirements will vary significantly depending on the unique needs of the job.
• Job assignments are usually for the summer or for short periods during breaks from school.
• Uses predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from structure and unstructured data.
• Develop software, algorithms and applications to apply mathematics to data, perform large scale experimentation and build data driven apps to translate data into intelligence, solve a variety of business problems and enable business strategy.
• Assists business with casual inferences; observations with finding patterns, relationships in data.
• Communicate results with internal business stakeholders
• This is an internship and compensation will be given accordingly based on candidate education level and internship duration.

Qualifications

• This position is not eligible for Intel immigration sponsorship.
• You must possess the below minimum qualifications to be initially considered for this position.
• Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
• Experience listed below would be obtained through a combination of your schoolwork and/or classes and/or research and/or relevant previous job and/or internship experiences.

Minimum Qualifications:

• Must be pursuing a Master's Degree with 6+ months of experience or Ph.D. Degree with 1+ year of experience in Statistics or Data Science or Operation Research or related field.

Preferred Qualifications:

• 6+ months of experience (master's) or 1+ year of experience (Ph.D.) with one or more of the following:
  • Statistical methodology/probability theory/linear models.
  • Relational database structures/research methods or machine learning/Cloud based technologies/Big Data technologies ( i.e. Hadoop/HBase/Lucene/Solr), analytics packages (i.e. R, Mahout/Matlab/Octave/Weka/scripting languages (i.e. Python/Perl)/programing language (i.e. Java/C/C++/SQL/SAS,/JMP/JSL/R.
  • Teaching or a teaching assistant experience at university level.