VUK DINIC

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WORK EXPERIENCE

Teaching Assistant/Junior researcher
Faculty of Philosophy, University of Niš - October 2020 - Present

  • Assisted in developing lesson plans and coordinated research activities for 500+ students annually, resulting in measurable improvements in academic outcomes.
  • Designed and implemented data-driven feedback systems, leading to a 20% improvement in curriculum quality.
  • Spearheaded the creation of a new methodology course, significantly enhancing student participation and engagement.
  • Applied quantitative and qualitative research methods to improve instructional strategies based on student feedback.

Data Analyst
Students For Liberty - September 2020 - February 2024

  • Developed data models and dashboards to inform strategic decisions, resulting in a 20% increase in revenue and enhanced volunteer engagement by 15%.
  • Conducted statistical analysis using Python and R, predicting volunteer retention rates with 90% accuracy, directly impacting organizational planning.
  • Led survey design and data collection efforts to assess program effectiveness, driving improvements across global volunteer programs.

EDUCATION

Master in Sociology, University of Niš - Graduation Date: October 2021

  • GPA: 9.29 (out of 10.00)
  • Science and Research Specialization

Bachelor with Honors in Sociology, University of Niš - Graduation Date: October 2020

  • GPA: 9.38 (out of 10.00)
  • Dositeja, Serbian Government Fund for Young Talents - Recognition of students earning a higher-than-average GPA
  • Best Graduate student of the department 2020
  • Best student of the department 2019
  • Best student of the department 2018

SKILLS

  • Programming Languages: Python, R, SQL
  • Statistical Software: IBM SPSS, Jamovi
  • Data Visualization: Tableau, PowerBI, Looker
  • Other Tools: Git, Linux, Jira, Salesforce
  • Research Skills: Quantitative and qualitative analysis, Statistical modeling, Survey design, Data visualization

PROJECTS

  • NLP analysis of the Serbian parliament

    Analyzed topics, sentiments, and speeches of the Serbian parliament sessions using NLP and Python. Work in progress.

  • Fashion MNIST Image Classification Project with PyTorch

    Implemented a Convolutional Neural Network (CNN) using PyTorch to classify images from the Fashion MNIST dataset, achieving high accuracy in image recognition.

  • Horizon

    Performed sentiment analysis as part of the EU Horizon 2020 project, using R programming to scrape data from Twitter and examined and interpreted the data, creating comprehensive reports that gave stakeholders important information.

  • Hackathon Finalist (Dialogue for the Future)

    Researcher on the team that developed a platform concept to support victims of domestic violence “Nisi sama”