Ranna Raabe

Software Engineer @ Uber

São Paulo, São Paulo, Brazil

About

Software Engineer at Uber team, working on the design and implementation of several features for Family and Teens product, and bachelor's degree focused in Computer Science from Federal University of Rio Grande do Norte.

Experience

  • Uber (São Paulo, São Paulo, Brazil)
    • Software Engineer II
      Sep 2025 - Present · 10 mos

    • Software Engineer I
      Feb 2024 - Sep 2025 · 1 yr 8 mos

    • Software Engineer Intern
      Mar 2023 - Jan 2024 · 11 mos

      Worked in the Family and Teens team, as an iOS mobile developer, improving the Uber for Teens product, focusing on giving an experience for teens and their caregivers, through selected partner drivers and escalation paths, as well as race visibility and security for those responsible.

  • Software Engineer Intern at Buzzmonitor
    Jun 2021 - Dec 2022 · 1 yr 7 mos

    Worked on the design and implementation of several features for improvement the Buzzmonitor system, a full and flexible platform for social media and multichannel service. Implemented post scheduling features for various social networks and optimizations for data loading, reducing the Buzzmonitor web page load, in the frontend with Ruby on Rails, Javascript and HTML, and in the backend using Ruby.

  • Instituto Metrópole Digital - IMD/UFRN (Natal, Rio Grande do Norte, Brazil · On-site)
    • Web Developer
      Apr 2020 - May 2021 · 1 yr 2 mos

      Developed a platform that gathers all data from epidemiological case notifications and monitoring from Rio Grande do Norte. Moreover, worked responsible for UI and UX of the platform, creating the visual identity for the whole system, in order to standardize the development of the platform interface. This project is a partnership between SESAP-RN and UFRN.

    • Machine Learning Researcher
      Jul 2019 - Mar 2020 · 9 mos

      Worked in scientific project that proposes a case study on semi-supervised models, especially Self Training, focusing on understanding and modifying aspects used in this type of algorithm so that it is possible to mitigate problems that are normally reported for this type of approach and possibly culminate in the study and improvement of the classification result for this type of algorithm.