Machine Learning and Data Management Challenges

Machine Learning and Data Management Challenges


How do the realities of Big Data World change VC investment optimization and create new challenges for machine learning and data management approaches?

Vitalii Bondarenko and Denys Osipenko will use a successful case of the VC investment company to answer this question and give recommendations on optimizing its performance under uncertainty. The speakers will share their insights from developing an intelligent machine learning platform and a set of models that utilizes a large amount of data to arrange prospective companies according to their investment attractiveness. 

Sign up if you are:

  • Data Engineer, Data Scientist, Data Analyst, Data Architect;
  • Data enthusiast;
  • A professional interested in Big Data and its application in business.


Vitalii Bondarenko has been designing data-centric systems for the last 20 years. Now, he is responsible for leading the Data and Analytics Centre of Excellence and building expertise in cloud data services.

Denys Osipenko has 15-year experience in Data Science. He was involved in Credit Scoring and Decision Making systems development for Retail Banking and Fintech, as well as worked as a Risk Modelling Manager. Now Denys is the Head of the Data Science Unit in Ciklum. 

Participation is free of charge.

Program of the webinar

  • The modeling target definition in conditions of uncertainty with business aims
  • Data set preprocessing issues for the data sources zoo
  • The modeling approach: the use of tree-based LGBM Classifier and K-Fold cross-validation
  • Data Architecture design and implementation with AWS technologies