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Amazon Internship | Data Science Internship for Students | Apply Before 25th July 2022

Amazon Internship | Data Science Internship for Students | Apply Before 25th July 2022

About the Data Science Internship:

Hi everyone , Amazon is hiring students for the role of Data Scientist Internship .This opportunity is for students so if you satisfy the eligibility then go ahead and apply for it.

One of the most complicated distribution systems in the world is being optimised by Amazon, who is looking for a data scientist. Computer science, engineering, operations research, or process control training and/or experience are highly suitable for this position.

Eligibility:

  • Startups
  • Undergraduate
  • Corporate
  • Engineering Students
  • Graduate

Highlights of Internship Program:

  • Application Deadline: 25 July 2022
  • Start Date: 4 July 2022
  • End Date: 25 July 2022
  • Location: Bengaluru, Karnataka, India

Responsibilities of the Candidate:

  • To provide technologies to improve customer experience and to inform company decision-making, use data analysis tools.
  • Generate new methods for planning and analysis, including understanding the sources and influencers of business-related issues.
  • To identify areas of opportunity and offer written business suggestions, identify, design, manage, and manage research.
  • Develop solutions using the highest levels of analytical discipline and data security while working with various teams as a leader of data study.
  • Analyze and address the fundamental causes of any strategic planning.

Requirements:

  • A track record of providing significant analytical solutions with business value.
  • Knowledge of SQL, SAS, MATLAB, and R.
  • Excellent grasp of Excel and other Microsoft Office programmes.
  • Possessing problem-solving skills and a love for large data.
  • Excellent communication and data presentation abilities.
  • English is spoken and written with easily.
  • Experience in data analysis and transformation, model training, pass, and large-scale deployment from academic studies.
  • Academic or Project Experience with MXNet, Tensor Flow, Caffe, and PyTorch.

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