The application period for the fifth edition of eMAG Talent Internship program is closed. If you are interested in our Internship program, write to us anytime at talent.internship@emag.ro
Data Analyst Development is a program for senior students willing to develop their competencies regarding data analysis. For 3 weeks, 3 people will participate on an accelerated learning process where they will discover the mysteries of SQL, MSSQL, MySQL or some reporting tools used by our Business Intelligence team.
After those 3 weeks, they will be assigned into teams, assigned to a mentor and working on projects that address real business needs. Data Analyst Development is a program that aims to develop the student's potential and offer them the context necessary to learn.
eMAG Commercial Traineeship is a development program in the commercial area in the largest e-commerce company in the region. For 6 months, 10 trainees have the chance to work with leading suppliers from all areas on the market, from IT to Fashion, from Mobile to Home & Deco.
Along with their mentors and the entire Commercial team, they learn about the processes underlying this department and contribute to the development of product categories available on eMAG.
eMAG Commercial Traineeship is one of the programs that bring us new colleagues, because after 6 months, the best performing of the 10 participants in the program become full time eMAG employees.
With the slogan: "Keep your brain fit!" we built "eMAG Workshops", a "hands on" learning program for students, based on a topic related to the online environment and using the latest technologies.
Structured in several dynamic meetings, the program brings together in one place eMAG mentors, IT specialists, and students who want to work on a theme prepared by the mentors. At the end of the program, the best of the participants automatically enter our internship program, eMAG Talent Internship.
The first edition of eMAG Workshops was held at the Faculty of Mathematics and Informatics, University of Bucharest, and explored the universe of recommendations often used in the online environment. In the end, the selected students learned how to build an online recommendations system.
