Machine Learning Engineer & Data Scientist with 4+ years delivering end-to-end AI solutions across finance, healthcare, and large-scale enterprise environments. Specializes in LLMs, RAG systems, ML pipelines, explainability, and high-impact automation. Published researcher with experience building production-grade platforms (NLP, speech AI, streaming analytics) and driving innovation through PoCs, cross-functional partnerships, and technical leadership. Passionate about applying advanced ML to real-world problems and scaling intelligent systems across organizations.
Professional Experience
Senior Machine Learning Engineer
Grid Dynamics
Dec 2025 - Present | Krakow, Poland
Designing, building and scaling production-grade AI/ML systems and infrastructure, with emphasis on enabling LLMs and advanced ML workflows.
- Architect and implement scalable ML infrastructure and tooling to support the full ML lifecycle — from data ingestion and preprocessing, through training/fine-tuning/evaluation, to deployment and monitoring. Build production-ready ML services: clean, maintainable and scalable codebases, API endpoints, model serving, CI/CD pipelines and deployment to cloud or containerized environments.
- Collaborate with stakeholders (product managers, architects, domain experts) to translate business requirements into ML/AI solutions — including LLM-based features, semantic search, RAG pipelines, and custom model workflows. Optimize model performance and compute efficiency, including distributed training, batch & streaming data pipelines, resource utilization, latency, and reliability for ML workloads.
Skills: Machine Learning Engineering, LLMs, RAG Systems, Semantic Search, MLOps, Distributed Training, Model Serving, CI/CD, Technical Leadership, Prompt Engineering
Tech Stack: Python, SQL (BigQuery, PostgreSQL, MySQL), Apache Spark, PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, NLP, Cloud Platforms (GCP, AWS), Docker, API Development, Data Pipelines, Model Deployment
AI Researcher for Mental Health Projects
Klimaka NGO
Mar 2025 - Present · 10 mos | Athens, Attiki, Greece · Remote
- Developing personalized mental health assessment tools using Large Language Models (LLMs), tailored to individual patient profiles.
- Ensuring GDPR compliance and ethical handling of sensitive mental health data.
- Conducting ML research on healthcare applications to improve clinical decision support.
- Developing a feedback loop between clinicians and AI tools to enhance question quality and clinical relevance.
Activities & Recognition:
- Delivered internal webinar: "Understanding AI – Applications in Psychology, Psychotherapy & Psychiatry" to 60+ participants.
- Collaborating with Laiko General Hospital to integrate dynamic questionnaires for use in emergency settings. [project]
- Contributing to the HygeIA first-aid mobile app, supporting suicide prevention through self-assessment tools and access to crisis resources; app won 2nd place in EIT Health i-Days 2025.
- Implementing an internal AI Platform to host all in-development AI tools as well as a centralized educational repository for internal knowledge sharing.
- KLIMAKA's Active Participation at the 33rd Panhellenic Psychiatry Congress (Ioannina, May 2025): Supported the presentation of pilot results from the "Anti-Suicide Shield" program at Laiko General Hospital, enhancing the visibility of the initiative and clinical data.
- Actively engaged in workshops, hands-on sessions, and collaborative projects at the EEBG 2025, applying genomics, metagenomics, transcriptomics, and LLM-based AI techniques to real-world bioinformatics challenges.
Skills: Large Language Models (LLM), Mental Health, Suicide Prevention, Project Management, Python, Data Analysis, Data Extraction, Data Processing, Version Control, Bioinformatics
Tech Stack: Python, OpenAI API, FastAPI, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers, Jupyter, Git, REST APIs, Mobile App Frameworks (Flutter/React Native), GDPR Compliance Tools, Data Visualization (Matplotlib, Seaborn, Plotly), Cloud Platforms (GCP, AWS)
Data Scientist (Automation & Analytics)
HSBC
June 2024 - Nov 2025 | Krakow, Poland
- Led 50+ QC Oversight sessions, 15+ analytical reviews, and multiple tool evaluations (Tesseract, AWS Textract, clustering, semantic similarity models), delivering dashboards, hybrid scoring frameworks, and process improvements adopted across A&A and RCAS teams.
- Developed 3+ major internal tools (QC Tracker, GenAI Solution Tracker, RCAS Resources Tracker), ran 20+ innovation sessions, automated data pipelines, and implemented prompt engineering & RAG architectures to optimize AI-driven compliance solutions.
- Leading analytical projects across investigations, intelligence delivery, transaction monitoring, network analytics, and other Compliance Analytics initiatives, delivering solutions to complex investigations across multiple lines of business.
- Developing end-to-end Data Science solutions and analytical models using statistical and machine learning techniques to provide actionable insights.
- Conducting multi-dimensional data analysis and visualizations, performing R&D using advanced statistical and mathematical modeling, and identifying process improvement opportunities to support proactive strategy building.
Activities & Recognition:
- Presented a semi-supervised ML project (complaints classification using sentiment analytics) at Krakow University of Economics (2025.01) and HSBC Summer School (2025.09). [presentation] [presentation]
- Represented HSBC at the UEK Job Fairs 2025, engaging with students and graduates on career opportunities in Risk, Compliance, Technology, Operations, and Finance. [volunteering event]
- Participated in 10+ mentoring and coaching sessions, competitions (Hackathon, Learning Hub, Agile May), and contributed to D&I initiatives and onboarding support, positively impacting teams of 4–8+ members.
Skills: Data Science, Machine Learning, Data Extraction, Data Analysis, Data Visualization, Automation, Compliance Adherence
Tech Stack: Python, SQL, Pandas, NumPy, SciPy, Git, scikit-learn, TensorFlow, Keras, BigQuery, GCP, Matplotlib, Seaborn, Plotly, Jupyter
Automation Specialist (Advanced Data Analytics)
Uber
Dec 2021 - May 2024 | Krakow, Poland
- Working with Central & Country teams to identify which processes should be automated
- Preparing tech documentation for the completed projects
- Measuring the business impact of my automation initiatives
Projects:
- Implemented and maintaining 25+ automation projects (real-time, non real-time)
- Project 1: Optimize Natural Language Processing (NLP) models to efficiently analyse drivers' open-end comments to understand patterns (topics clustering, sentiment) and increase DSAT (Driver Satisfaction)
- Project 2: Optimise current Tabular Data Models to efficiently analyse restaurants features to understand patterns (feature importance) and predict the probability of churn, to enhance restaurants retention and satisfaction
Tech Stack:
- Programming Languages: Python, SQL and JavaScript (Google Scripts)
- APIs: AWS S3, Google (Sheets, Drive, Email), Apache Kafka, Kirby (for Hive tables), Apache Thrift, QueryRunner (for Presto and Pinot), Grafana, Google BigQuery
- Common Libraries: NumPy, Pandas, Scikit Learn, NLTK, seaborn, requests, typing
- Extra Tools: uWork, Logger, Docker, Phabricator
Local Operations Intern
Uber
Mar 2021 – Sep 2021 | Athens, Greece
- Analyzed rider and driver behavior using Advanced SQL and Python to extract business insights.
- Identified areas for operational improvement through data-driven recommendations.
- Designed and implemented a Taxi Fare Estimation optimization project for Athens & Thessaloniki to (1) improve user experience and (2) reduce fraud.
Tech Stack: Python, SQL, Pandas, NumPy, Google Sheets, Jupyter, Tableau
Machine Learning Research Assistant
Biomedical Research Foundation, Academy of Athens
Sep 2021 - Dec 2021 | Athens, Greece
- Developed and published a web-based tool for COVID-19 severity prediction using machine learning. [Google Scholar] [DOI] [pdf] [website]
- Conducting research on the effects of various factors in Parkinson's disease onset and progression, applying machine and deep learning techniques.
- Applied feature importance analysis, visual explanation techniques, and embedding methods for Parkinson's classification using raw tabular data from the Greek Parkinson Database.
- Built and tested machine learning pipelines for tabular data, including data preprocessing, model evaluation, and iterative optimization.
- Collaborated with interdisciplinary teams to integrate bioinformatics insights into ML models.
Activities & Recognition:
- Presented a poster at the 6th HBP Student Conference on Interdisciplinary Brain Research. [poster]
- Research highlighted in peer-reviewed publication: "A machine-learning-based web tool for the severity prediction of COVID-19"
- Actively contributing to an ongoing manuscript on Parkinson's disease progression using machine and deep learning.
Tech Stack: Python, Scikit-learn, XGBoost, Keras, Pandas, NumPy, Matplotlib, Seaborn, Jupyter, Git
Data Science Intern
National Center for Scientific Research "Demokritos"
Sep 2019 - Oct 2019 | Athens, Greece
- Developed diagnostic classification models for Alzheimer's disease using the Pitt Corpus dataset, which contains text and audio data from Alzheimer's patients.
- Performed comprehensive data preprocessing including text normalization, feature extraction, and handling of imbalanced datasets with limited sample sizes.
- Implemented cross-validation strategies to address the small sample size challenge, ensuring robust model evaluation despite limited data availability.
- Applied advanced NLP and ML models including LSTM, CNN, and BERT for multi-modal classification of Alzheimer's disease from patient transcripts and speech patterns.
Tech Stack: Python, TensorFlow, PyTorch, Hugging Face Transformers, Librosa, Scikit-learn, NLTK, Pandas, Jupyter
Education
PhD in Bioinformatics
Ionian University
2025 – Present | Corfu, Greece
Advancing AI for Integrative Bioinformatics in Precision Medicine
- Developing a robust, scalable, and interpretable multi-modal AI framework to integrate text, images, and tabular data for predictive analytics in precision medicine, addressing key gaps in current bioinformatics methodologies.
- Incorporating advanced techniques in deep learning, natural language processing (NLP), and image analysis, including convolutional neural networks (CNNs) for medical image analysis and transformer-based models for clinical text processing.
- Analyzing tabular omics data (genomic and proteomic) using hybrid models that combine statistical techniques with machine learning algorithms.
- Implementing innovative methods such as transfer learning and few-shot learning to handle small, heterogeneous datasets common in bioinformatics, enhancing model robustness when large annotated datasets are unavailable.
- Developing explainable AI methods for multi-modal biomedical data using state-of-the-art techniques (SHAP values, Grad-CAM) to provide insights into how different data modalities contribute to model predictions, improving trustworthiness and clinical usability.
- Exploring the application of large language models (LLMs) with retrieval-augmented generation (RAG) for integrating knowledge from external sources, enabling the system to access and incorporate current medical literature and omics databases.
- Pioneering adaptive learning algorithms specifically designed for healthcare, capable of continuously updating and refining knowledge bases as new medical research and clinical data become available, using meta-learning and few-shot learning techniques.
Research Focus: Multi-modal AI, Explainable AI, Precision Medicine, Bioinformatics, Deep Learning, NLP, Medical Image Analysis, LLMs, RAG Systems
MEng, Electrical and Computer Engineering
National Technical University of Athens
2015 – 2022 | Athens, Greece
- Major: Computing & Software Systems (GPA: 9.1/10.0, Top 5%).
- Thesis: "Machine & Deep Learning Classification and Visual Explanation of Dyslexia and Spelling Deficiency Using fMRI Data" [pdf] [slides]
Skills: Data Processing, REST APIs, Bioinformatics, Deep Learning, Data Science, Data Analysis, Data Visualization, Statistical Modeling, Machine Learning, MLOps, Version Control, TensorFlow, Computer Vision, Apache Spark, SQL, Data Extraction, NLP, Python, Signal Processing, Git
Minor in Finance
American College of Greece (Deree College)
2017 – 2020 | Athens, Greece
- Focused on Finance and Data Analytics (GPA: 3.82/4.00).
Skills: Data Processing, Data Science, Data Analysis, Data Visualization, Machine Learning, Portfolio Management, Data Extraction, Python, Git
Summer School in Foundations of Neuroscience
Harvard University (Remote)
2021 | Online
- Completed Foundations of Neuroscience Summer Program with SNF/ACG Scholarship.
Skills: Data Processing, Data Analysis, Data Visualization, Data Extraction, Python
Skills
Technical Skills
Programming & Scripting Languages
Python
C/C++
SQL
MATLAB
Java
HTML/CSS/JavaScript
Bash/Shell
Google Apps Script
Machine Learning & AI
TensorFlow 2.x
Keras
PyTorch
Scikit-learn
🤗 Hugging Face Transformers
XGBoost
LightGBM
OpenAI API
MLflow
Data Engineering & ETL
Pandas
NumPy
SciPy
OpenCV
Apache Airflow
Apache Kafka
Apache Spark
Hive
REST APIs
JSON/XML
Shell scripting
Visualization & Reporting
Matplotlib
Seaborn
Plotly
Tableau
Grafana
Google Data Studio
Excel / Google Sheets
Cloud & Infrastructure
Google Cloud Platform
AWS S3
Heroku
VPS (Ubuntu)
Docker
GitHub Actions
Tools & Development Environments
Git
GitHub
VS Code
PyCharm
Conda
virtualenv
Languages
Greek
Native
English
Fluent
French
Intermediate
Spanish
Intermediate
Honors & Awards
BR4N.IO Hackathon x IEEE-SMC-2025 | 1st Place 🥇
Worldwide: 1st place in the Data Analysis category
Participation: Among 69 teams and 404 participants from 50+ countries 🌍
Event: Brain ECoG Hackathon 2025, organized by g.tec medical engineering GmbH and IEEE SMC, Vienna, Austria 🧠🏆
Associated with: Klimaka NGO
Issued by: g.tec medical engineering GmbH, IEEE SMC · Oct 2025
CERTIFICATE: View Certificate
EIT Health i-Days 2025 | 2nd Place 🥈
Nationwide: 2nd place 🏆
Participation: Among 11 teams across undergraduate and postgraduate programs
Event: i-Days 2025, organized by EKT & EIT Health, in collaboration with National & Kapodistrian University of Athens (NKUA) 🌟
Project: HygeIA – AI-powered first-aid app providing step-by-step basic life support guidance and connecting users to 112, leveraging a Greek Large Language Model (LLM) 🤖
Associated with: Klimaka NGO
Issued by: EIT Health, Eθνικό Κέντρο Τεκμηρίωσης και Ηλεκτρονικού Περιεχομένου - National Documentation Centre (EKT) · Nov 2025
CERTIFICATE: View Certificate
Honorary Award | Ministry of Education & Eurobank EFG
Recognized for achieving the highest Nationwide University Entrance Examination Score at my Senior High School.
Scholarship | Stavros Niarchos Foundation (SNF)
Scholarship for Parallel Studies at Deree – The American College of Greece.
Competition Award | IEEE NTUA SB
2nd place in "IEEEXtreme 13.0" algorithmic programming competition.
Volunteering & Activities
Volunteer
- Organization: Wheeling2Help NGO
- Period: Jan 2024 - Present
- Responsibilities: Focusing on community empowerment, I engaged in environmental conservation, sports development, and educational support initiatives. This experience deepened my understanding of sustainable development and reinforced my commitment to meaningful change.
Marketing Coordinator
- Organization: CogniHub (Interdisciplinary Non-Profit Student Organization)
- Period: Jan 2021 - Nov 2023
- Responsibilities: Conducting competitive marketing research and organizing events.