Andriy Trofimov

Director, Software Engineering @ EPAM Ukraine

Head of Lviv Delivery Office

Topic: “EPAM Development Strategy and Challenges”

Taras Myklush

Director, Software Engineering @ EPAM Ukraine

Topic: “Intelligence Enterprise Practice Overview”  

Bohdan Hay

Software Engineering Manager @ EPAM Ukraine

“IEP projects breakdown”

TBD

Jonathan Rioux 

Lead Data Scientist @ EPAM Canada

Former insurance professional, reformed data scientist, I’ve been with many companies on their journey to “data science readiness”. I’ve been doing research on the human factors of machine learning, such as privacy, interpretability and adoption, as well as their impact on model performance.

“Data Science from the trenches: getting your client data science ready”

Data science is the cool kid in the block: every company wants to do it. Then why is it so hard to go from idea to production? Most often, client ambitions don’t match their ability to execute, and they often misunderstand the journey from where they are to where they should be. This talk will focus on common hurdles, and how you can be a key part in ideating, executing and delivering amazing data science projects.

Dmytro Yatsyuk

Lead Systems Engineer @ EPAM Saint Petersburg

• I have 15+ years of supporting huge production environments,  5 years as Lead L3 support.
• For the last 5 years have worked intensively with and gained expertise in Apache Hadoop products.

“Analytics with Azure Databricks. The way to success, and challenge”

In my talk I want to discuss business drivers and goals, functional and non-functional requirements,  solution Architecture overview (technology stack and nuances,  technology stack and nuances based on HDI cluster,  Azure DevOps and Databricks flow, Azure DevOps and running job on Databricks), delivered Business value, lessons learned (lessons learned: communications, lessons learned: monitoring, lessons learned: cloud maintenance, lessons learned: Databricks integration and automation), why the project is interesting to me.

Volodymyr Fedorchuk

Project Manager @ EPAM Ukraine

16+ years of commercial experience in software development starting from system engineering, software development, to delivery management. In BigData since 2013, focused on health care and genetic projects.

“BigData in Genetics” (or + “or a data lake in my pocket”)

1. What is genetic data
2. Computer code vs genetic code
3. Nature/characteristics of genetic data
4. Data access patterns
5. Technical solutions

Renat Gilmanov

Senior Solution Architect @ EPAM Ukraine

Last four years have been busy developing a next-generation e-commerce search for a huge retail company. Interested in simplicity and computer vision.

“Computer vision on the edge”

Computer vision continues to expand its influence and to transform industries. Digital cameras are cheap and rapidly becoming ubiquitous. There are many aspects to consider regarding how this process will change the way we live. Will it make our lives not only easier but also more interesting?

Video

Oleh Hrynyk

Senior Solution Architect @ EPAM Ukraine

Oleh has spent more than 12 years building distributed systems, defining technical landscapes and architecting entire solutions while considering all aspects including security, HA, performance and adaptability. Over the course of his career, he has tried various technical stacks, including dotnet, eCommerce, front-end, rdbms, API-to-data and ml. Currently, Oleh is coordinating data and architecture competencies in Lviv, but he’s still managing to find time for hands-on coding while working on consulting, architecture activities and more.

“DATA ENGINEERING IN 2019”

In my talk I want to discuss how people solve data-related problems and deal with complexities. How to build a modern data platform and what the prerequisites for this are. As not always you can start building data platform, which might lead to slow dev cycles and/or team idling.

• Overview of trends in data engineering
• Clear data engineering misconceptions
• Review data platform components
• Deep dive into data engineering solutions