📊 Miriam Stoehr – Data Analytics & Data Science Portfolio

📍 Brussels, Belgium

🔗 LinkedIn

About Me

I am a data analytics trainee and aspiring data scientist with a strong analytical background, currently transitioning into the tech industry. My foundation bridges political science, economics, and cultural studies, complemented by hands-on experience in finance, accounting, and controlling. This interdisciplinary perspective helps me approach complex questions with a data-driven and structured mindset.

In my previous roles in finance and business operations, I identified inefficiencies in data handling and reporting workflows, leading initiatives that improved data integration, transparency, and collaboration. These experiences sparked my interest in using data and technology to drive smarter decision-making.

Currently, I am enhancing my technical skills through the BeCode Data Science & AI Bootcamp, where I work on applied projects involving machine learning, data analysis, and interactive dashboards. I am especially interested in roles where I can combine analytical thinking, technical tools, and domain knowledge to apply data science in ways that solve real problems, improve processes and contribute to positive, tangible change.

🛠 Skills & Technologies

• Programming Languages: Python, SQL, Basics in HTML, CSS, JavaScript, C

• Data Analysis & Visualization: Pandas, NumPy, Matplotlib, Seaborn, Power BI, Excel, Streamlit, Geopy, Folium

• Machine Learning & AI: Scikit-learn, PyTorch, DBSCAN, NLP, Sentiment Analysis, Regression, Clustering

• Data Collection & APIs: FastAPI, Web Scraping (BeautifulSoup, Selenium, Scrapy), REST APIs

• Cloud & Infrastructure: Basic AWS knowledge

• Version Control & Collaboration: Git, GitHub, SharePoint

💼 Projects

 

🔐 AI-Generated Phishing Awareness Campaign

Team Project – BeCode Bootcamp, inspired by real-world cybersecurity challenges faced by organizations in Belgium

• Used Gophish and its API to configure campaign parameters (recipients, templates, click/report tracking)
• Integrated OpenAI & Gemini APIs to generate dynamic phishing emails
• Developed a Streamlit dashboard to receive and visualize campaign data
• Tools Used: Python, Gophish API, OpenAI API, Gemini API, Streamlit
  🔗 Campaign Repo | Dashboard Repo

🏠 Real Estate Price Prediction – End-to-End Pipeline

Team & Solo Project – BeCode Bootcamp

1. Data Collection (Team)

• Scraped Belgian property listings using dynamic/static scraping; structured the dataset for analysis
• Tools Used: Python, Selenium, BeautifulSoup, Pandas
  🔗 Repo

2. Data Cleaning & EDA (Team)

• Cleaned and analyzed data, visualizing trends in location, pricing, and features
• Tools Used: Python, Pandas, Matplotlib, Seaborn
  🔗 Repo

3. Model Development (Solo)

• Engineered geospatial and categorical features; trained & validated KNN regression model
• Tools Used: Python, Scikit-learn, Geopy, DBSCAN, OrdinalEncoder, StandardScaler
  🔗 Repo

4. Model Deployment (Solo)

• Built a Streamlit app with map integration for user-driven property price predictions
• Tools Used: Python, Streamlit, Folium
  🔗 Streamlit App | Repo

📈 Reddit Sentiment Analysis

Solo Project – NLP Focus

• Collected Reddit posts via API and applied sentiment scoring to identify user attitude trends
• Visualized sentiment distribution across subreddits and over time
• Tools Used: Python, NLP, Pandas, Matplotlib
  🔗 Repo

💞 Relationship Clustering Analysis

Solo Project – BeCode Bootcamp

• Analyzed the HCMST dataset to uncover demographic and behavioral patterns in relationship formation
• Used clustering to identify five distinct relationship profiles based on age, income, meeting context, and duration
• Tools Used: Python, Pandas, Scikit-learn, Seaborn
  🔗 Repo

📚 Wikipedia Web Scraper

Exploratory Research Tool

• Scraped and processed Wikipedia articles to support research-driven text analysis
• Tools Used: Python, BeautifulSoup, Pandas
  🔗 Repo

🎓 Learning & Certifications

• BeCode Data Science & AI Bootcamp – Full-time, project based training in data analysis, data science, machine learning, and AI.

• CS50’s Introduction to Computer Science (Harvard/edX) – Core CS & coding foundations (C, Python, SQL, HTML, CSS, and JS).

• Python for Everybody (University of Michigan/Coursera) – Python and data structures.

• Ongoing learning – via DataCamp, Kaggle, a.o.

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🚀 What I’m Looking For

I’m seeking opportunities in data analytics, machine learning, or research analysis—particularly roles that let me apply data to solve meaningful real-world challenges such as fraud prevention, process optimization, or policy support.

📫 Let's Connect!

Feel free to reach out via LinkedIn or GitHub for collaboration opportunities or discussions on data science and AI.

Note: Some of these projects were developed during use case collaborations at BeCode. While inspired by real-world challenges, no proprietary or confidential information from any external partner has been used.