Position: Head of R&D
Category: Lead
English level: upper
Years of experience: 11

- At least the five data science-based products and services have been delivered to end-users and customers around the World. 
- Over 8 innovative projects have been launched from scratch. 
- Over 10 new technologies have been researched and applied to innovative products and services.
- Over 10 presentations have been made at the international conferences related to Data Science, BigData and Digital Signal Processing topics (AI Ukraine, AI&BigData, Dessert etc).
- Over 5 educational programs have participated: Summer Data Science School at UKU, IT and AI for Pupils (Bucha Ukrainian Gymnasium), Deep Learning open lectures (NTUU KPI), Samsung Smart classes (NTUU KPI, Taras Shevchenko National University), etc
- Head of data science / Project Tech Lead - leading data-science based projects and multifunctional teams (up to 25 engineers and data scientist). Doing requirement and system analysis especially the data science-related projects. Developing microservice architecture considering DDD (CQRS, event-sourcing microservices, dataservices). Leveraging BigData technologies and ETL (Spark, Kafka, ELK, Neo4j). Social media analytics with NLP and CV. Leading R&D activities. Cloud-native architectures, Kubernetes. CI&CD based on Jenkins X and Kubernetes, infrastructure as code, MLOPS.

- Director of Research at Ring - Managing and Leading the R&D team (up to 20 engineers and researchers). Building the R&D processes. Researching shallow and deep
learning technologies for suspicious activity detection and crime recognition: computer vision, audio data, data mining. Developing distributed high-load services for AWS.

- Head of R&D Laboratory at Samsung - Managing and Tech Leading the R&D laboratory (up to 50 engineers). Project management, budgets, requirement and risk analysis. Managing worldwide dataset gathering.  R&D Areas: Data Science, Shallow Machine Learning, Deep Machine Learning, Pattern recognition. Product Areas: Sport and Health-oriented applications, Sensor recognition, OCR. Technology stack: C++, Java, Python, Android SDK, Android NDK.  Cluster for ML and MLOPS  based on Mesos, Spark, Cassandra