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  • Job Context

    We are seeking a passionate AI and Data Science Intern to join our team. This internship offers hands-on experience in AI algorithms, machine learning models, and data analysis techniques. The ideal candidate is enthusiastic about AI and Data Science, eager to learn, and ready to contribute to impactful projects.

  • Job Responsibility

    • Work closely with our AI and Data Science team to develop and implement machine learning algorithms and models.
    • Conduct data analysis, data cleaning, and preprocessing tasks.
    • Assist in building and maintaining data pipelines for data collection, processing, and storage.
    • Collaborate on research projects and experiments to explore new AI techniques and methodologies.
    • Participate in code reviews, testing, and documentation efforts.

  • Educational Requirement

    Preferably B.Sc. in Computer Engineering or Science or similar discipline.


    • Strong programming skills in Python and familiarity with libraries such as NumPy, Pandas, and Scikit-learn.
    • Understanding of machine learning algorithms and techniques.
    • Experience with data visualization tools like Matplotlib or Seaborn.
    • Knowledge of SQL and experience with relational databases.
    • Excellent analytical and problem-solving skills.
    • Ability to work independently and collaboratively in a team environment.
    • Enrollment in or recent completion of a degree program in Computer Science, Data Science, Statistics, or related field.

  • Experience Requirement

    0-1 year(s)

  • Additional Requirement


    The trainee is required to pay 4000 EGP refundable commitment fees. the fees will be refunded after completion of the internship with progress higher than 90%. this to make sure that the trainee is committed to the training program.

  • Others Benefits


Dead Line Expired

Jobs Information

  • Company Name

    Niotek
  • Job Category

    Internship
  • Job Position

    Intern
  • Job Type

    internship
  • Salary

    NA
  • Job Location

    Remote
  • Deadline

    15 May 2024