Hi, I'm Alexandros Polyzoidis.

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Skilled in building scalable solutions for e-commerce and logistics. Proficient in Python, SQL, Azure, and deep learning frameworks. Passionate about solving real-world problems through data-driven insights and model deployment.

About

I am a Data Scientist skilled in machine learning, cloud services, and building impactful solutions for e-commerce and logistics. My expertise includes Python, SQL, PowerBI, and Azure tools like Data Factory, Synapse Analytics, and Databricks. I have experience with projects in customer segmentation, credit card fraud detection, and image classification for damaged goods. My work has focused on NLP and computer vision, helping to develop scalable solutions that address real-world challenges.

  • Quantitative Analysis: Mathematics, Statistics
  • Programming Languages: Python, R, SQL
  • Machine Learning & Deep Learning: Scikit-learn, PyTorch, TensorFlow, Keras, etc.
  • Data Visualization: Tableau, Power BI, ggplot2, matplotlib, seaborn
  • Cloud & Big Data: Azure ML Studio, Synapse Analytics, Databricks, Data Factory
  • Tools & Software: GitHub, Jupyter, RStudio, VS Code, PgAdmin, Postman
  • Soft Skills: Critical Thinking, Communication, Collaboration

Currently, I am working as a freelance data scientist and seeking an opportunity to join a data science or machine learning team where I can contribute, learn, and grow in a dynamic environment.

Experience

Data Scientist
  • Developed and implemented customer segmentation models for e-commerce clients, enhancing targeted marketing and personalization strategies.
  • Created computer vision solutions for supply chain and logistics companies, including image classification to detect damaged loads during loading and unloading processes.
  • Leveraged Python, Scikit-learn, and Azure ML Studio to build scalable models; utilized Tableau and Matplotlib to present insights effectively.
  • Tools: Python, Scikit-learn, Tensorflow, Keras, Pytorch, Azure ML Studio, Tableau, Matplotlib, PowerBI
October 2023 - Present | Remote
SaaS B2B Sales & Strategy Analyst, Revenue Department
  • Conducted exploratory data analysis and applied K-means clustering to segment prospective clients and prioritize leads, contributing to an annual revenue growth nearing €400,000.
  • Utilized Tableau and Power BI to visualize key sales metrics, generate actionable insights, and inform strategic decisions, optimizing outreach efforts.
  • Leveraged Odoo CRM to manage daily activities, accurately forecast pipelines, and develop data-driven quotes and proposals.
  • Tools: Tableau, Power BI, Odoo CRM, Python, K-means Clustering
January 2022 - May 2024 | Thessaloniki, GR
Account Manager
  • Enhanced client relationships by implementing data-driven strategies, resulting in a 20% increase in client satisfaction ratings.
  • Utilized Entersoft CRM software to track client interactions and identify trends for targeted strategies.
  • Collaborated with the analytics team to analyze sales data and provide personalized recommendations to clients.
  • Tools: Entersoft CRM, Data Analytics, Client Relationship Management
May 2021 - January 2022 | Thessaloniki, GR
Transportation Manager
  • Coordinated and planned transport activities for the Packed-Goods Transport Department, increasing on-time delivery rates by 15%.
  • Minimized empty cargo trips by 20% by strategically reorganizing truck schedules based on customer demand and inventory levels.
  • Streamlined route planning for 50+ vehicles using GPS and optimization software, boosting delivery efficiency by 25% and cutting fuel use by 15%.
  • Tools: GPS, Route Optimization Software, Data Analytics, Excel
April 2018 - August 2019 | Thessaloniki, GR

Projects

Petra Reviews Sentiment Analysis
Petra Reviews Sentiment Analysis

An end-to-end AI application that classifies visitor reviews into positive, neutral, or negative sentiments.

Accomplishments
  • Tools: FastAPI, PyTorch, Docker, Transformers (Hugging Face), Jinja2, Chart.js, Python
  • Achieved ~90% accuracy using optimized transformer-based models.
  • Interactive web interface with sentiment trend visualization.
  • Deployed using Docker on Heroku for scalability and ease of access.
Endangered Species Classifier
Endangered Species Classifier

A deep learning model to identify endangered animal species based on image classification.

Accomplishments
  • Tools: TensorFlow, Python, Streamlit, Heroku, ResNet50, OpenCV, NumPy, Keras, MLflow, Matplotlib, Docker
  • Classifies species with high confidence using transfer learning.
  • Visually appealing web interface with responsive design for ease of use.
Emotion Image Classifier
Emotion Image Classifier

A deep learning project that classifies the emotion (Happy or Sad) in uploaded images.

Accomplishments
  • Tools: TensorFlow, Python, FastAPI, Heroku, Docker, OpenCV, NumPy, Keras, MLflow, Matplotlib,
  • Achieved high accuracy with MobileNetV3 architecture, optimized for performance.
  • Supports batch processing and ZIP uploads for efficient classification.
Credit Card Fraud Detection
Credit Card Fraud Detection

A deep learning model in PyTorch designed to classify fraudulent credit card transactions.

Accomplishments
  • Tools: Python, PyTorch, SMOTE, Scikit-learn, Matplotlib
  • Trained deep learning model to detect fraud in transactions.
  • Balanced dataset with SMOTE, achieving high precision and recall.
quiz app
Card Deck-Image Classification

An image classification project that identifies different cards in a deck using PyTorch.

Accomplishments
  • Tools: PyTorch, Python, Image Classification, Computer Vision, Convolutional Neural Networks (CNNs)
  • Created custom dataset class for efficient card image handling.
  • Achieved 97% accuracy using EfficientNet-B0 and custom classifier.
Screenshot of web app
Titanic Survival Prediction

A predictive model using machine learning techniques to estimate passenger survival likelihood on the Titanic.

Accomplishments
  • Tools: Python, Scikit-learn, Classification, Data Preprocessing, EDA
  • Predicted Titanic survival using machine learning models.
  • Achieved 81% accuracy for survival prediction.
Screenshot of  web app
Digit Recognizer-LSTM Model

A sequence model built with LSTM to classify handwritten digits from the MNIST dataset.

Accomplishments
  • Tools: Scikit-learn, Python, Classification, Data Preprocessing, Exploratory Data Analysis (EDA)
  • Preprocessed and loaded handwritten digit images efficiently.
  • Achieved 97.83% test accuracy with an LSTM classifier.
Screenshot of  web app
Soil Types Identification Analysis

A machine learning model to classify soil types based on physical and chemical soil properties.

Accomplishments
  • Tools: R, KMeans Clustering, ggplot2, factoextra
  • Cleaned and scaled soil data for accurate k-means clustering.
  • Identified optimal clusters, visualized using ggplot2 for insights.
Screenshot of  web app
Countries Visitation Analysis

An analysis project to explore visitation data and trends across different countries.

Accomplishments
  • Mined frequent country visitation patterns with Apriori algorithm in R.
  • Discovered strong visitation link between Cyprus and Greece.
  • Tuned parameters to refine travel insights from association rules.
Screenshot of  web app
Abalone Age Prediction

Uses regression models to predict the age of abalones based on physical measurements from a dataset.

Accomplishments
  • Built a linear regression model to predict abalone age based on physical measurements, achieving strong accuracy through feature selection.
  • Applied PCA to reduce dimensionality, balancing model interpretability with a slight trade-off in predictive accuracy.

Skills

Quantitative Analysis and Programming Languages

Python
R
MySQL
PostgreSQL
Mathematics
Statistics

Libraries

NumPy
Pandas
OpenCV
Scikit-learn
Matplotlib
Seaborn

Frameworks

Flask LogoFlask
Keras LogoKeras
TensorFlow LogoTensorFlow
PyTorch LogoPyTorch
Bootstrap LogoFastAPI

Cloud & Big Data

Azure LogoAzure
Databricks LogoDatabricks
Synapse Analytics LogoSynapse Analytics
Data Factory LogoData Factory

Development & Deployment Tools

Postman LogoPostman
Docker LogoDocker
Heroku LogoHeroku
MLflow LogoMLflow

Tools & Software

Git LogoGit
Jupyter LogoJupyter
VS Code LogoVS Code
PgAdmin LogoPgAdmin
Power BI LogoPower BI
Tableau LogoTableau

Soft Skills

Critical Thinking IconCritical Thinking
Communication IconCommunication
Collaboration IconCollaboration

Education

Hellenic Open University

Patra, Greece

Degree: Master of Data Science & Machine Learning

    Relevant Courseworks:

    • Machine Learning & Data Mining
    • Deep Learning for Computer Vision
    • Statistical Data Analysis
    • Big Data Technologies & Cloud Computing
    • Natural Language Processing

Aristotle University of Thessaloniki

Thessaloniki, Greece

Degree: M.Sc. in Logistics & Supply Chain Management

    Relevant Courseworks:

    • Supply Chain Analytics
    • Inventory & Warehouse Management
    • Logistics Optimization Techniques
    • Transportation Planning & Operations
    • Quantitative Methods in Supply Chain

Aristotle University of Thessaloniki

Thessaloniki, Greece

Degree: B.Sc. in Finance

    Relevant Courseworks:

    • Financial Management
    • Corporate Finance
    • Investment Analysis
    • Accounting Principles
    • Economics & Quantitative Methods

CERTIFICATIONS

  • Microsoft Certified: Azure Data Scientist Associate – Microsoft, 2024
  • Python A-Z™: Python for Data Science with Real Exercises! (Udemy)
  • 15 Days of SQL: The Complete SQL Masterclass 2024 (Udemy)
  • Tableau A-Z: Hands-On Tableau Training for Data Science (Udemy)
  • R Programming A-Z: R for Data Science with Real Exercises (Udemy)

Contact