Mission Statement
Data scientist (PhD) with 5+ years of experience building and deploying production ML systems. Experience designing scalable pipelines that process billions of data points and turning research prototypes into production-grade systems. Deep expertise in data quality, entity resolution, and duplicate detection. Production experience with embeddings and vector search, plus recent work in LLM application development 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)
- Was part of a team that built the ML models matching and clustering medical activities into expert profiles – embedding-based candidate retrieval, similarity ranking with gradient boosted trees, and entity resolution – processing up to 20 billion activity pairs per run and generating millions of automated profiles across US, EU, LATAM, and APAC regions.
- Transformed exploratory Jupyter Notebook prototypes into production-ready PySpark + Airflow pipelines on AWS EMR, with MLflow for experiment tracking and model deployment, Docker and Kubernetes for containerized services, testing, monitoring, and CI/CD integration, collaborating with cross-functional engineering teams.
- Balanced a three-way trade-off between precision, recall, and manual-curation cost, using threshold-based quality tiers to hold 99% precision while reducing manual curation costs by up to 70%.
- Organized Data Science meetups, technical talks, and team activities to promote knowledge sharing and strengthen engineering culture.
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 at scale.
- 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
ML & Data
Infrastructure & DevOps
Databases
Data Quality
AI & LLMs
Certificates
AI & LLM Engineering (Udemy)
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
Deep Learning Specialization
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
Intensive German Course – Levels A2.2, B1.1, B1.2
Die Neue Schule, BerlinPhD (Dr. rer. nat.) in Information Systems – Data Preparation & Domain-Agnostic Duplicate Detection
Hasso Plattner Institute (HPI), University of Potsdam – Digital Engineering FacultyMSc in Informatics (Information Systems) – Theta-Joins on MapReduce
Aristotle University of Thessaloniki (AUTH), School of InformaticsBSc in Informatics (Information Systems) – Recommender System on MapReduce
Aristotle University of Thessaloniki (AUTH), School of Informatics10 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