Data Scientist | Athina, Greece 10 Jan, 2022 - 4 Mar, 2022

Employer: AIESEC in Romania
Domain:
  • Others
  • Job type: internship
    Job level: Student/Graduate
    Location:
  • Abroad
  • Updated at: 30.07.2021
    Short company description

    AIESEC este o organizatie studenteasca existenta la nivel global, structurata ca o platforma de oportunitati pentru tineri, care isi desfasoara activitatea in 126 de tari si teritorii, si in peste 1000 de centre universitare. Organizatia este condusa in intregime de studenti si are ca obiectiv principal dezvoltarea de lideri care sa aducă un impact pozitiv in societate. In acest scop, membrii ei lucreaza pe arii precum Resurse Umane, Finante, Marketing sau Vanzari, au sansa de a coordona echipe, de a crea proiecte si de a face stagii de voluntariat sau internship-uri profesionale în oricare din tarile in care AIESEC este prezent. Organizatia exista in Romania din anul 1990, infiintandu-se in Bucuresti iar mai apoi deschizand alte 15 comitete locale in alte 13 orase din Romania, si anume in Arad, Brasov, Constanta, Cluj, Craiova, Galati, Iasi, Oradea, Pitesti, Sibiu, Suceava, Targu-Mures, Timisoara.

    Requirements

    Backgrounds
    Computer sciences
    Statistics
    Skills

    Data Analytics
    Data Analysis
    Data Science

    Languages
    English

    Minimum study level
    Bachelor

    Responsibilities

    Data scientists help organizations to solve vexing problems. Combining computer science, modeling, statistics, analytics, and math skills—along with sound business sense—data scientists uncover the answers to major questions that help organizations make objective decisions.

    Working hours
    Monday to Friday, 10:00am - 6:00pm

    Responsibilities
    Develop a comprehensive and deep understanding of the crop modelling data we work with and foster learning with colleagues using analytical tools and applications to broaden data accessibility and advance the company's proficiency/efficiency in understanding and appropriately using the data.
    Stay current with and adopt emergent analytical methodologies, crop modelling tools and applications to ensure fit-for-purpose and impactful approaches. Choosing and using the right analytical approach for each task.
    Apply rigor in analytical methods; plan for data processing; design a fit-for-purpose analysis plan.
    Communicate findings to the team and participate in meetings to present your insights.

    Achievables:
    Produce downscaling for two provided regions from two gridded climatic variables
    Produce gridded maps from historical weather station data of two provided regions