CIC’s Data Scientist, Max Kulinich, is available to provide you support in data-driven analysis and development projects, and to work with you on how to capitalize on available data and extract valuable insights.
Max’s background is in Mathematics and Data Analysis. He has an M.Sc. in Complex Adaptive Systems from the University of Gothenburg, Sweden and is doing a PhD in Mathematics at the University of New South Wales. He previously worked as a Senior Data Scientist at AB Volvo for 12 years and specialized on data visualization, statistical analysis and machine learning. Much of his work involved developing new methods for data extraction, interpretation and presentation to support multi-million business decisions and drive high customer satisfaction. Since starting at UTS in 2019, most of his work has been focused on rapid prototyping of new data visualization solutions, applying rigorous statistical analysis for better understanding of the UTS student population and developing machine learning recommendation systems.
Working with UTS Faculties and Business Units
With an extensive background in various business development projects, Max is eager to share his knowledge and experience with UTS Faculties and Business Units staff on:
- General consultation about internal data-sets, statistics and analytics
- Support and quality assurance of data-intensive development projects
- Locating, accessing and utilizing internal UTS data-sets to support data-driven decisions
- Production of interactive data visualizations and detailed reports
Working with UTS Researchers
With his research experience, Max is ready to consult with UTS staff on research matters, including:
- Handling Data (merging, cleaning, enhancement etc.)
- Statistical analysis of data at a research level (e.g. Design of Experiments, Anomaly detection, etc.)
- Model fitting and model evaluation (e.g. Decision Trees, Logistic Regression, Neural Networks, etc.)
- Application of machine learning algorithms including rapid prototyping and hyper-parameter tuning
- Statistical analysis of survey data of various types
- Production of statistical and analytics visualizations
- General advice on the applicability of all the above to specific projects
Contact Max on max.kulinich@uts.edu.au