I am a Data Scientist currently working at Pfizer. I have an MSc in Mechanical Engineering from the Aristotle University of Thessaloniki. I have several years of experience in data science, specifically in developing and deploying machine learning models, data exploration and analysis, and data visualization. I am passionate about using data to drive business decisions and improve operations.

• Python
Proficient in Python and experienced with various libraries and frameworks for data analysis and machine learning, such as Numpy, Pandas, Seaborn, Sklearn, TensorFlow, etc.

• Deep Learning Frameworks & architectures
Familiar with multiple DL frameworks such as Tensorflow, Keras, PyTorch, and architectures such as CNN, RNN and GAN.

• Athena/Redshift/Snowflake SQL
I have experience working with SQL and am able to efficiently retrieve and manipulate data for analysis.

• Dataiku Data Science Studio (DSS)
Experienced with DSS for data management, preprocessing, and model deployment.

• React/Dash
Experience with front-end development using React/Dash.

• Flask/Rest API
Experience with back-end development using Flask.

Project 1: Mimic III Full Stack application

The goal of this application is to analyze the correlation between patients' interactions and the duration of their hospital stay. By utilizing data from the MIMIC III database and implementing a full stack solution, this project aims to provide valuable insights for healthcare professionals to optimize patient care and reduce length of stay.

Project 2: COVID-19 Forecasting

This project utilizes time series analysis to forecast the number of COVID-19 cases for the next 30 days. By implementing the Facebook Prophet model and utilizing real-world data, this project aims to provide insight into the potential spread of the virus and assist in pandemic response planning.

Project 3: MNIST Image Classification

This project explores the use of convolutional neural networks (CNNs) for image classification, specifically on the MNIST dataset. By implementing a CNN architecture inspired by LeNet-5, this project aims to demonstrate the effectiveness of CNNs for image recognition tasks and serve as a foundation for further research in the field.

Please visit my Full Portfolio for more information and other projects.