Christina Voskoglou

Christina leads the analyst team and oversees all VisionMobile data projects (big or small!), from design to methodology, to analysis and insights generation. She is also behind VisionMobile’s outcome-based developer segmentation model, as well as the Developer Economics reports and DataBoard subscription services. While at VisionMobile, Christina has led data analysis, survey design and methodology for the ongoing Developer Economics research program, as well as several other primary research projects. Prior to joining VisionMobile, Christina served as Customer Relationship Manager for the Household Lending Unit of EFG Eurobank Ergasias. Her role placed her in charge of defining a CLV-based approach to managing customers and designing & supervising all direct marketing campaigns. Christina has more than 16 years of experience in statistical consulting, business & customer intelligence design, data mining and business analysis & forecasting. She holds an MSc in Statistics from the London School of Economics (LSE) and a BSc in Economics & Statistics from the University of Bath.

Christina Voskoglou

Data scientists need to make sense of the big picture, rather than the big data

The web echoes with cries for help with learning data science. “How do I get started?”. “Which are the must-know algorithms?”. “Can someone point me to best resources for deep learning?”. In response, a bustling ecosystem has sprung to life around learning resources of all shapes and sizes. Are the skills to unlock the deepest secrets of deep learning what emerging data scientists truly need though? Our research has consistently shown that only a minority of data scientists are in need of highly performing predictive models, while most would benefit from learning how to decide whether to build an algorithm or not and how to make sense of it, rather than how to actually build one.

What is the best programming language for Machine Learning?

Q&A sites and data science forums are buzzing with the same questions over and over again: I’m new in data science, what language should I learn? What’s the best language for machine learning?