Career Profile
With a PhD in AI and an Executive MBA in Digital Entrepreneurship, I offer a unique blend of technical expertise in data science and machine learning engineering, coupled with profound comprehension of business complexities and requirements. My experience spans data science, machine learning, and project management, with a focus on bridging business and technical teams. I thrive on collaborative efforts and have a proactive approach to problem-solving, ensuring project success.
Experiences
Deeply Project: Online Reputation Management Application for Tourism Professionals
- Participation in the project scoping phase and contribution to the platform design.
- Close collaboration with the executive team and business units.
- Expertise in data science: identifying data sources, defining key metrics for online reputation evaluation, specifying data analysis algorithms, including aspect-based sentiment analysis.
- Active development of key components of the solution.
- Tech Stack : Stack technique : Python, SQL, Scrapping, Selenium, NLP, Sentiment Analysis, Hugging Face Transformers, FastAPI, Airflow, Pytest, ELK Stack, GCP, Docker, Kubernetes Git/Gitlab.
DATAMOTOR Project : Sales Forecasting and Pricing Optimization for a Physical Clothing Store
- Collaborating with client teams to understand and articulate their needs.
- Collecting and cleaning data from multiple sources to ensure quality and consistency.
- Designing and developing Machine Learning models to forecast in-store sales and optimize pricing strategies.
- Deploying ML models into production and monitoring their performance.
- Tech Stack : Python, SQL, Time Series, Pandas, Scikit-Learn, ARIMA, FB Prophet, XGBoost, Tensorflow Data Validation (TFDV), MLFlow, Airflow, FastAPI, Pytest, ELK Stack, PostgreSQL, GCP, Docker, Kubernetes, Git/Gitlab.
Co-founder of a deep tech startup named “Closanet”
- Closanet offers advanced recommendations based on image and language processing for online shopping.
- Designing the IT infrastructure and modeling the data pipeline.
- Writting functional specifications and product backlogs.
- Developing an image processing module for fashion trend analysis.
- Managing a team of three people and completed a POC.
- Tech Stack : Python, Java, Visual Computing, NLP, Keras, PyTorch, Selenium, Spring Boot, Postgresql, Elasticsearch, Heroku, Git. Agility, Scrum, Kanban, Trello
PICS Project: Personal Information Controller Service
- Design and development of a personal data search module on the web, powered by a privacy risk score.
- Completion of the POC, mockup modeling, experimental validation, server configuration, solution deployment, and deliverables documentation.
- Tech Stack : Java, Python, Scrapping, Selenium, Apache TIKA, ETL, NLP, Privacy, Micro-services, Elasticsearch, Postgresql, NGINX, Balsamiq
- Participated in the development of Cyprus ERP, a software designed for the retail industry to better manage retail stores
- Tech Stack: Java, SQL, JSF, Hibernate, Spring, Oracle, Maven, Git/SVM
Certifications
Training program offering specialization in the field of management and digital marketing for promoting businesses in the digital era.
- Company Audit, Market Analysis, Entrepreneurship & Management, Project Planning & Management, KPIs & Dashboarding.
- Preparation for agile management of cross-functional teams, development of robust business plans, and planning of viable projects.
- Final Project: “Proposal for a repositioning strategy for a Startup dedicated to managing the online reputation of tourism professionals for better differentiation in the market.”
Real-world experimentation with end-to-end ML on Google Cloud. This specialization have teached me how to:
- build Vertex AI AutoML models without writing a single line of code;
- build BigQuery ML models knowing basic SQL;
- create Vertex AI custom training jobs that I deployed using containers using Docker;
- use Feature Store for data management and governance;
- use feature engineering for model improvement and determine the appropriate data preprocessing options for your use case;
- use Vertex Vizier hyperparameter tuning to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems,
- use Vertex AI prediction and model monitoring services to help manage the performance of our ML models.
I learnt how to use Spark SQL and Delta Lake to ingest, transform, and query data to extract valuable insights that can be shared with my team.
Projects
This is some of my personal and professional projects. Some of them are hosted on Github and are publically accessible. **This section is under construction**
Publications
This section showcases a selection of my scientific publications produced during my PhD research. More publications could be found at my ResearchGate page