Timur Kulenović
Machine Learning Engineer
Ljubljana, Slovenia
Download PDFWork Experience
SportradarLjubljana, Slovenia
Machine Learning Engineer2023 — Now
- Synthesizing real-time market data and betting liabilities to automate optimal odds compilation.
- Implementing player profiling models enabling automated account limits and fraud detection.
- Engineering automated trading triggers to monitor liabilities and manage house exposure.
Telekom SlovenijeLjubljana, Slovenia
Data Scientist2020 — 2022
- Developed ML models predicting the probability of customers leaving the company — churn models.
- Clustering of IPTV users for the purpose of segmentation.
Education
Faculty of Computer Science and Informatics, University of LjubljanaLjubljana, Slovenia
M.Sc. in Data Science and Computer ScienceOct. 2020 — Ongoing
- Data Science master program is part of DataScience@UL-FRI and focuses on data analysis, statistics and machine learning.
Faculty of Computer Science and Informatics, University of LjubljanaLjubljana, Slovenia
B.Sc. in Computer ScienceOct. 2017 — Sep. 2020
Skills
- Programming
- Regular usage of Python, R, Java and SQL.
- Machine learning
- Knowledge of various ML methods. Flink. Kafka.
- Environments
- Comfortable in macOS and Linux (Ubuntu).
- Languages
- English, Slovenian, Bosnian, German (basic).
Publications
Analysis of home advantage in sportsMaster Thesis · 2023
- Addressed home advantage in professional basketball and football leagues, focusing on five top-level leagues in each sport. The main goal was to quantify home advantage and compare it between the leagues.
Analysis of tourist movements with the help of Geocaching gameDiploma Thesis · 2020
- Geocaching is an outdoor game in which players search for hidden caches at outdoor locations with the help of a website and mobile application. Used web scraping to collect the data users enter into the application and then analyzed the collected data.
Featured projects
Basketball and Football dataset2022
- Collection of high-granularity data of basketball and football matches obtained using web scraping.
Clustering web users based on mouse movement2021
- The objective was to classify web users into groups by performing clustering on their mouse movement data.
Predicting Bundesliga matches outcome2020
- Collected data of German Bundesliga matches and used it to build ML models. The goal was to predict match outcomes by creating a three-class classification problem.
Timur Kulenović · Curriculum Vitae