Diana Jaganjac
About Diana Jaganjac
Diana Jaganjac is a Data Analyst with expertise in programming languages and machine learning. She holds an MSc in Data Science from Birkbeck, University of London, and has worked in various roles related to data analysis and environmental science.
Work at Disperse
Diana Jaganjac has been employed as a Data Analyst at Disperse since 2022. In this role, she applies her expertise in data analysis and programming to support the company's objectives. Her work involves leveraging data to drive insights and improve decision-making processes within the organization. Disperse focuses on utilizing technology to enhance construction project management, and Diana's contributions are integral to the data-driven strategies employed by the company.
Education and Expertise
Diana Jaganjac holds a Master of Science in Data Science (Hons) from Birkbeck, University of London, which she completed in 2020. She also earned a Bachelor of Science in Physical Geography (Upper Second Class Honours) from King's College London, graduating in 2017. Her educational background includes a study abroad program at the University of Melbourne, where she studied Physical Sciences. Diana specializes in programming languages such as Python, R, SQL, and noSQL, along with machine learning, cloud computing, Git, and Linux.
Background
Diana Jaganjac's professional journey includes various roles that have shaped her analytical skills. She worked as a Language Consultant at what3words in 2019 and as a Marketing Communications Intern at the International Commission on Missing Persons in 2017. Additionally, she served as an Environmental Data Scientist at CGG from 2020 to 2021 and as a Data Administrator at King's College London from 2017 to 2019. Her internships at the Post-Conflict Research Center and as an Environmental Science Research Assistant at the University of Melbourne further contributed to her diverse experience.
Projects and Research
Diana Jaganjac is currently developing a master's project that integrates satellite remote sensing with machine learning to predict changes in atmospheric pollution over time. This project builds on her previous work, where she developed an artificial neural network model to calculate atmospheric pollution from space. During her undergraduate studies, she also completed a project utilizing geographical information systems (GIS) and data analysis, achieving top marks for her efforts.
Interests and Continuous Learning
Diana Jaganjac has a strong interest in expanding her technical skill set. She actively seeks to learn new programming languages, frameworks, and principles to enhance her capabilities as a data analyst. This commitment to continuous learning reflects her dedication to staying current in the rapidly evolving field of data science and analytics.