Mission Statement
Senior Data Scientist (PhD) with 5+ years of industry experience building and deploying production ML systems, most recently in life sciences. Specialized in data quality and entity resolution, with additional experience in embeddings, vector search, LLM applications, and agentic systems.
Experience
Senior Data Scientist / Data Scientist
Veeva Systems – Link ProductSenior Data Scientist (Mar 2024 – Feb 2026) · Data Scientist (Dec 2021 – Feb 2024)
- Models: Trained and fine-tuned entity-resolution models to match and cluster medical activities into expert profiles, using embedding-based candidate retrieval followed by ranking with gradient-boosted trees (XGBoost).
- Results: Achieved 99% precision while reducing the need for manual review. Quality thresholds determined which matches were automated and which required manual review, with precision and recall evaluated against human-annotated data.
- Scale: Matched millions of activity pairs in recurring runs and billions during periodic profile creation, generating millions of expert profiles across US, EU, LATAM, and APAC.
- Production: Turned Jupyter prototypes into production PySpark and Airflow pipelines on AWS EMR, using MLflow, Docker, Kubernetes, testing, Grafana monitoring, and CI/CD. Optimized Spark performance and cluster costs while collaborating with cross-functional engineering teams.
- Team: Organized Data Science meetups and technical talks.
Data Engineer / Full-Stack Engineer
HPI Schul-Cloud – Dataport- Built and maintained data pipelines for 300k+ educational assets, improving structure, reliability, and discoverability for end users.
- Implemented systematic data preparation, cleaning workflows, and duplicate-detection methods to ensure data quality.
- Contributed across the full stack (Python, Vue.js, PostgreSQL, Docker, Kubernetes) to maintain and scale the educational platform.
- Led technical requirements clarification, team operations, and onboarding during a multi-month organizational transition.
Research Consultant
SAP & SAP Concur- Developed 3 novel ML pipelines in Python and Java to improve duplicate detection, increasing matching success by 18%.
- Delivered on-site technical tutorials at SAP Concur Seattle (USA) on data matching classification and pipeline optimization.
Technical Skills
Programming Languages
Python
SQL
Java
JavaScript
C/C++
ML & Data
PySpark
scikit-learn
XGBoost
PyTorch
Pandas
NumPy
Hugging Face Transformers
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
Embeddings
Vector Search (Qdrant)
AI & LLMs
Large Language Models
LangChain
LangGraph
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
Together, these courses provided a comprehensive refresher on deep learning fundamentals and further expanded my knowledge of modern deep learning models.
Education
Intensive German Course – Levels A2.2, B1.1, B1.2
Die Neue Schule, BerlinIntensive German language course in Berlin, progressing through levels A2.2, B1.1, and B1.2.
PhD (Dr. rer. nat.) in Information Systems – Data Preparation & Domain-Agnostic Duplicate Detection
Hasso Plattner Institute (HPI), University of Potsdam – Digital Engineering FacultyThesis on Data Preparation and Domain-Agnostic Duplicate Detection, supervised by Prof. Felix Naumann. Defended with distinction (Magna cum Laude). Published 7 papers in top-tier journals and conferences. Organized 6 project seminars on Duplicate Detection, Data Preparation, Blockchain, Text Mining, and Recommender Systems.
Read dissertationMSc in Informatics (Information Systems) – Theta-Joins on MapReduce
Aristotle University of Thessaloniki (AUTH), School of InformaticsImplemented thesis in Python, Java, and Hadoop; published in top-tier conference. Awarded State Scholarship Foundation scholarship. Vice Chair of local ACM Student Chapter. Participated in ACM SIGMOD 2013 programming contest (streaming system in C++).
Read thesisBSc in Informatics (Information Systems) – Recommender System on MapReduce
Aristotle University of Thessaloniki (AUTH), School of InformaticsImplemented thesis in Java and Hadoop; published in top-tier journal. Interned at IT Center performing system and database administration.
Read thesis (in Greek)Publications
10 peer-reviewed papers across BSc, MSc, and PhD research — 6 journal articles and 4 conference papers on entity resolution, duplicate detection, data preparation, and data quality.
Journals — ACM Journal of Data and Information Quality (×3) · ACM Transactions on Database Systems · Distributed and Parallel Databases (Springer) · Expert Systems with Applications (Elsevier)
Conferences — VLDB · EDBT/ICDT · Italian Symposium on Advanced Database Systems (SEBD) · International Workshop on Data Science for Macro-Modeling
Languages
🇬🇷
Greek
Native
🇬🇧
English
Fluent
🇩🇪
German
Intermediate (B1)