Digital Analytics and Machine Learning Pipelines for Online Gaming Data Monetization
Conference (ADVANCED level)
Skalkotas
Online betting is an emerging field of entertainment and as a result data size and complexity spikes up exponentially especially since lockdowns.
Competitors crucial need is to digest this data "big bang" by quickly understanding customer behavioral patterns and leverage the ability to satisfy users in speed and relevance.
OPAP Online analytics team showcases how tech streams, ML/AI methodologies and recommender systems, structure a streamline synergy impacting directly users devices, maximizing data monetization potential through faster and personalized user experience.
Competitors crucial need is to digest this data "big bang" by quickly understanding customer behavioral patterns and leverage the ability to satisfy users in speed and relevance.
OPAP Online analytics team showcases how tech streams, ML/AI methodologies and recommender systems, structure a streamline synergy impacting directly users devices, maximizing data monetization potential through faster and personalized user experience.
Manos Nikolopoulos
OPAP
Manos Nikolopoulos is a Digital Marketing and Data Science expert, working on the eCommerce industry for the last 13 years.
After witnessing the birth and evolution of the Digital Marketing domain, he changed his focus towards leveraging Machine Learning and AI, to try and take this domain to the next level.
One Master's degree and six years into this pursuit later, the fruits of his new endeavors are now ripe for the use.
In his current role, Manos leads a team of data scientists who are using advanced ML and AI techniques in the vast world of digital data, analyzing and predicting the users future browsing behavior, setting the foundations for a machine based digital marketing strategy with smart and data driven decisions
After witnessing the birth and evolution of the Digital Marketing domain, he changed his focus towards leveraging Machine Learning and AI, to try and take this domain to the next level.
One Master's degree and six years into this pursuit later, the fruits of his new endeavors are now ripe for the use.
In his current role, Manos leads a team of data scientists who are using advanced ML and AI techniques in the vast world of digital data, analyzing and predicting the users future browsing behavior, setting the foundations for a machine based digital marketing strategy with smart and data driven decisions
Christos Platias
OPAP SA
Christos Platias, MSc, is the Online Data Analytics and Insights Manager at OPAP, overseeing the operations of pamestoixima.gr. He holds a Bachelor's degree in Mathematics from the University of Athens, an MSc in Applied Statistics, and an MSc in Enterprise Risk Management.
With over 8 years of experience in Data Analytics across industries such as Gaming/Gambling and Customer Relationship Management (CRM), Christos has developed deep expertise in Artificial Intelligence (AI) and Machine Learning (ML) development.
He has extensive experience in the design, implementation, and optimization of AI/ML models, with a particular focus on developing advanced propensity and segmentation models, recommendation engines for best-next offers, and deep learning techniques. Additionally, Christos is highly skilled in the deployment of ML Ops pipelines, ensuring the seamless integration, monitoring, and scalability of AI/ML models.
His work spans both structured and unstructured data manipulation, leveraging advanced statistical and database management tools. Christos is committed to driving strategic insights and decision-making by bridging the intersection of business, analytics, AI, and design.
With over 8 years of experience in Data Analytics across industries such as Gaming/Gambling and Customer Relationship Management (CRM), Christos has developed deep expertise in Artificial Intelligence (AI) and Machine Learning (ML) development.
He has extensive experience in the design, implementation, and optimization of AI/ML models, with a particular focus on developing advanced propensity and segmentation models, recommendation engines for best-next offers, and deep learning techniques. Additionally, Christos is highly skilled in the deployment of ML Ops pipelines, ensuring the seamless integration, monitoring, and scalability of AI/ML models.
His work spans both structured and unstructured data manipulation, leveraging advanced statistical and database management tools. Christos is committed to driving strategic insights and decision-making by bridging the intersection of business, analytics, AI, and design.