Nicolae Righeriu

Bis 2019, Msc. Data science, Technische Universiteit Eindhoven and Universidad Politecnica de Madrid

München, Deutschland

Fähigkeiten und Kenntnisse

Softwareentwicklung
Python
JavaScript
Latex
Machine Learning
pandas
scikit-learn
keras
Java

Werdegang

Berufserfahrung von Nicolae Righeriu

  • Bis heute 3 Jahre und 10 Monate, seit Sep. 2020

    Data engineer

    Allianz Digital Health

  • 10 Monate, Nov. 2019 - Aug. 2020

    Software Engineering Consultant

    AKKA Consulting GmbH

    - Maintaining and extending a MS-Access database - Courses on project management and experience with agile methods - Participating in workshops about soft-and consulting skills - Developing innovation projects with intercultural teams in various fields

  • 7 Monate, Jan. 2019 - Juli 2019

    Data Science Intern

    Vizzuality

    -Building a global land cover classifier using recent satellite images -Writing and testing microservices for parallel computation using Google Earth Engine, Python -Geodata processing with geopandas: tidying, processing or simplifying raw geographical formats -Performing analyses and creating statistical graphics to expose data in a usable manner

  • 7 Monate, Jan. 2017 - Juli 2017

    Student research assistant

    TU Berlin

    -Programming a Java GUI for recording simulation results in databases -Building a Java tool for registering data tags in C2Mon -Software based actuation of hardware components in the lab

  • 7 Monate, März 2016 - Sep. 2016

    Software tester

    Intellic GmbH

    -Writing and automating test cases in Python while analyzing product requirements -Ensuring product quality

Ausbildung von Nicolae Righeriu

  • 2 Jahre, Sep. 2017 - Aug. 2019

    Msc. Data science

    Technische Universiteit Eindhoven and Universidad Politecnica de Madrid

    Master of Science with a third of entrepreneurship. Subjects such as Process mining, Data Engineering, Large Scale Data Management, Applied statistics, Time series forecasting, Innovation & Entrepreneurship, Massively Parallel Machine Learning, Data Analysis.

  • 3 Jahre und 11 Monate, Sep. 2013 - Juli 2017

    Computer Science

    TU Berlin

    Artificial intelligence, Data Analysis, Stochastics, Data structures, Logic, Computer networks, Scientific Computing, Computer architecture, System programming. Thesis: Development of a hybrid filter-wrapper feature selection approach for short-term load forecasting

Sprachen

  • Deutsch

    Fließend

  • Englisch

    Fließend

  • Rumänisch

    Muttersprache

  • Spanisch

    Fließend

  • Niederländisch

    Grundlagen

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