Junior Data Analyst - Internship

Acest job nu mai este activ!

Vezi toate job-urile Pirelli active.


Vezi toate job-urile Junior Data Analyst - Internship active pe Hipo.ro

Vezi toate job-urile in IT Software active pe Hipo.ro

Angajator: Pirelli
Domeniu:
  • IT Software
  • Tip job: practica
    Nivel job: Student/Absolvent
    Orase:
  • Craiova
  • Actualizat la: 04.04.2018
    Scurta descriere a companiei

    After 10 YEARS, Pirelli plant in Slatina is today one of the most modern car tyre plants, equipped with non-robotic production technology of the last generation, designed to achieve high performance ti res Premium range, where Pirelli is leader.

    Cerinte

    Ideal qualification, experiences and attitudes:

    • Degree in Mathematics, Computer Science, Information Management, or related area.
    • Very good command of English, spoken and written.
    • Attitude to work in team.
    • A high attention to detail.
    • Strong analytical and problem solving skills.
    • Be flexible and adaptable in approach to role.

    Desirable Skills

    • Computer skills in Excel and some knowledge of business intelligence and data visualization tools (e.g. QlickView, OBIEE, Oracle, Oracle Data Integration…).
    • Strong analytical skills and ability to collect, organize, analyze hard data and soft information.
    • Good written and verbal communication and presentation skills.
    • Flexibility, availability, ability to multi-task.
    • Ability to identify improvement areas and to proactively suggest and implement changes.

    Responsabilitati

    Key responsibilities include:
    Inspecting, cleaning, updating data coming from different sources before they can be used for forecasting and analysis.
    Reporting data issues, identification and implementation of corrective actions through connection with people internal to the organization.
    Preparation of reports for internal stakeholders, either updating existing reports or providing data to ad-hoc enquiries.
    Identification of new data sources and processes to help streamline the data quality and completeness efforts.
    Extract, cleanse, transform and load data from external sources.