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Dimitrios G.
Data Scientist
Dimitrios is a Data Scientist with over seven years of commercial experience delivering predictive models, analytical pipelines, and data-driven solutions.
He specialized in Python, SQL, Scikit-learn, and Google Cloud to develop forecasting, churn, and segmentation models that enhanced decision-making and drove tangible business outcomes.
At ESL FACEIT Group, he developed player behavior and matchmaking models deployed through Vertex AI. At Channel 4, his ad performance models contributed to generating more than £8 million in additional revenue.
Dimitrios combined deep analytical expertise with practical engineering skills, turning complex datasets into actionable insights and measurable results.
Main expertise
- SQL 7 years
- Python 7 years

- Data Science 7 years
Other skills
- Git 7 years

- Bash 3 years

- Google Cloud Storage 3 years
Selected experience
Employment
Data Scientist
ESL Faceit Group - 3 years 1 month
ESL FACEIT Group is a leading global gaming company operating major competitive esports platforms and tournaments.
- Developed and deployed a user segmentation model using unsupervised clustering to group players by recency and activity frequency, enabling personalized reactivation campaigns, which resulted in 3× higher conversion rates and sustained engagement uplift over 10 days.
- Designed the Fast Skill Calibration model to estimate true skill levels for new players, addressing the Cold Start Problem in matchmaking through supervised predictive modeling.
- Created a Trust Score metric for behavioral analysis over a rolling ten-match window, which helped identify and reward positive player behavior and reduced disruptive incidents.
- Partnered with analytics, product, and growth teams to integrate models into production, supporting decision-making and targeted communications.
- Managed data pipelines in Google Cloud (Vertex AI, BigQuery) for large-scale model training and real-time analytics.
Technologies:
- Technologies:
MySQL
PostgreSQL
Python
- Data Science
Google Cloud
NumPy
XGBoost
Pandas
PyCharm
Machine Learning
Large Language Models (LLM)
Vertex AI
Jupyter
Google Cloud Storage
- A/B Testing
Data Scientist
Channel 4 - 1 year 6 months
Channel 4 is a UK public-service broadcaster leveraging advanced analytics to optimize audience experience and advertising efficiency.
- Built Impact Forecasting models using supervised learning to predict the performance of commercial breaks by demographic, generating over £8M in additional revenue during 2021.
- Created Ad Load Optimization models to determine ideal ad frequencies per user, maximizing lifetime value while preserving viewer experience.
- Engineered large-scale MCMC simulations using Dask and PySpark, reducing computation times by 40%.
- Delivered explainable models and reporting dashboards for business and sales teams.
- Supported the migration of on-premises data pipelines to AWS Lambda and EC2, streamlining model deployment.
Technologies:
- Technologies:
AWS
Python
AWS Lambda
AWS S3
- Data Science
NumPy
Pandas
PyCharm
Scikit-learn
- Data Modeling
Machine Learning
AWS EC2
Jupyter
Data Scientist
Virgin Media - 1 year
Virgin Media is a UK-based broadband and telecommunications company serving millions of residential and enterprise customers.
- Developed acquisition models using supervised learning to identify high-probability prospects, improving customer acquisition rates by 22%.
- Created proactive churn and upsell models to enhance customer retention and cross-sell effectiveness.
- Designed a feature engineering framework leveraging Dask for parallelized processing on large datasets, accelerating feature computation by 5×.
- Delivered real-time predictive services integrated with marketing automation pipelines.
Technologies:
- Technologies:
MySQL
PostgreSQL
Python
- Data Science
XGBoost
Scikit-learn
- Data Modeling
Machine Learning
Jupyter
Junior Data Scientist
JustPark - 1 year 5 months
JustPark is a UK-based smart parking platform connecting drivers with parking spaces through real-time digital solutions.
- Conducted customer segmentation (KYC) using clustering and classification to predict lifetime value and improve user targeting.
- Built demand-supply optimization models that identified profitable expansion regions across the UK, supporting data-driven market growth.
- Produced data reports and dashboards shared with B2B clients to evaluate partnership performance and business viability.
- Automated recurring analytics workflows in Python, saving hours of manual reporting each week.
Technologies:
- Technologies:
MySQL
Python
- Data Science
XGBoost
Pandas
PyCharm
Scikit-learn
- Data Modeling
Jupyter
Data Scientist Assistant
JustPark - 2 months
-
Conducted research and modeling as part of MSc dissertation in collaboration with JustPark.
-
Designed a customer segmentation pipeline (clustering) using unsupervised learning to identify patterns in user parking behavior.
-
Produced actionable recommendations for marketing and retention teams.
-
Wrote and presented a dissertation project applying the methodology to real company data, later used internally for campaign targeting.
Technologies:
- Technologies:
MySQL
Python
- Data Science
XGBoost
Pandas
PyCharm
Scikit-learn
- Data Modeling
Machine Learning
Jupyter
-
Education
MSc.Big Data Science and Technology
University of Bradford · 2017 - 2018
BSc.M.Eng Computer and Communications Engineering
University of Thessaly · 2007 - 2017
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