Mission Statement
Machine learning engineer (PhD) with 5+ years of experience building and deploying production ML systems at scale. Deep expertise in data quality, entity resolution, and duplicate detection. Actively exploring LLMs and agentic AI to deliver intelligent automation.
Experience
Data Scientist / Senior Data Scientist
Veeva SystemsCreating and updating profiles of medical experts (Health Care Professionals – HCPs) while continuously monitoring and ensuring high data quality.
- Processing millions of Health-Care Professionals’ activities (e.g., publications) to create and update millions of professional profiles.
- Analyzing data to assess quality and support decisions, training machine learning models on large-scale curated datasets, and deploying them to production.
- Turning ideas into experiments in Jupyter Notebooks and building production-grade, resilient PySpark pipelines. Tech stack includes AWS, Apache Airflow, Kubernetes, Docker, and more.
Data Engineer / Full-Stack Engineer
HPI Schul-CloudManaged data workflows and improved content quality for the HPI SchulCloud platform, delivering content to multiple states and their schools across Germany.
- Imported and scraped data using Scrapy; managed the platform’s database and content infrastructure based on Tomcat, PostgreSQL, and ElasticSearch.
- Improved data quality through validation, enrichment, and consistency checks.
- Supported multiple teams, broadening my full-stack expertise—from DevOps (Docker, Kubernetes) to backend development (JavaScript, later TypeScript), and front-end development (Vue.js, Next.js), as well as writing unit and end-to-end tests using Cucumber (Gherkin).
Research Consultant
SAP ConcurIn the first three years of my PhD, in collaboration with SAP and in particular SAP Concur, we develop approaches to perform data cleaning and deduplication on hotel datasets provided by our partners from Concur. Several methodologies were developed and the most notable ones produced two publications. Doing an applied PhD was a remarkable experience to get hands-on knowledge.
Technical Skills
Programming Languages
Python
SQL
Java
JavaScript
C/C++
ML & Data
PySpark
scikit-learn
PyTorch
Pandas
MLflow
Apache Spark
Apache Airflow
Infrastructure & DevOps
AWS (EMR, S3)
Docker
Kubernetes
CI/CD
FastAPI
Git
pytest
Databases
PostgreSQL
MongoDB
Data Quality
Entity Resolution
Duplicate Detection
Record Linkage
Data Cleaning
Data Preparation
AI & LLMs
Large Language Models
LangChain
Agentic AI
Certificates
AI & LLM Engineering (Udemy)
Udemy ∙
October 2025
Completed during July - October 2025 a comprehensive series of courses covering modern AI engineering practices:
Courses completed:
- AI Automation: Build LLM Apps & AI-Agents with n8n & APIs - Practical LLM automation for daily tasks including Telegram voice messages, Google Calendar booking, and email management
- The Complete Agentic AI Engineering Course - Built multi-agent systems using OpenAI, CrewAI, LangGraph, and MCP. Created sales agents, deep research tools, stock pickers, and 4-agent engineering teams
- LLM Engineering: Master AI, Large Language Models & Agents - Explored multi-modality, RAG pipelines, model fine-tuning, and multi-agent systems for product price optimization
- LangChain: Develop AI Agents with LangChain & LangGraph - Implemented Chain of Thought, ReAct, and Few Shot techniques. Built RAG pipelines with vector databases and worked with Model Context Protocol (MCP)
Generative AI with Large Language Models
Coursera ∙
July 2025
Three-week course covering the complete LLM lifecycle: Transformer architecture and pretraining, fine-tuning techniques including Parameter Efficient Fine-Tuning (PEFT) with LoRA and Soft Prompts, and Reinforcement Learning with Human Feedback (RLHF). Explored Chain-of-Thought reasoning and the ReAct framework that underlies modern agentic AI systems.
Deep Learning Specialization
Coursera ∙
January 2021
Foundational specialization from Coursera on Deep Learning. Comprised of the following courses:
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
- Structuring Machine Learning Projects
- Convolutional Neural Networks
- Sequence Models
Through it I got a hollistic refreshment and further expansion of my knowledge on the primary Deep Learning fundamentals and models.
Education
PhD in Information Systems
Hasso Plattner InstituteThesis on Data Preparation and Domain-Agnostic Duplicate Detection. Supervised by Prof. Felix Naumann. Published 7 papers in top-tier journals and conferences.
Read dissertationMSc Computer Science
Aristotle University of ThessalonikiSpecialized in Data Engineering and efficient calculation of Theta-Joins on large-scale data using Apache MapReduce.
Read thesisBSc Computer Science
Aristotle University of ThessalonikiThesis on Recommender Systems on large-scale data using Apache MapReduce.
Read thesis (in Greek)Languages
🇬🇷
Greek
Native
🇬🇧
English
Fluent
🇩🇪
German
Beginner