Hi 👋, I’m Stephan!

What do I do? I solve problems using data! I specialize in improving process quality in manufacturing and tackling challenges across various fields, including social media, video games, and e-commerce.

Currently, I work as a data scientist in manufacturing and quality assurance. My role involves:

• Developing business intelligence solutions (e.g., KPI dashboards) for internal and external stakeholders
• Building machine learning applications and optimisation models for monitoring and quality assurance using web-based platforms.

I earned my PhD in Computer Science from the University of Melbourne, where I gained extensive experience in data analysis and data profiling as part of the Melbourne eResearch Group.

Teaching and sharing knowledge is another passion of mine. I teach machine learning and love simplifying complex data through clear, impactful visualizations. Teaching not only helps me share knowledge but also deepens my understanding. As Einstein said: “If you can’t explain it simply, you don’t understand it well enough.”

To stay sharp, I regularly explore diverse datasets, read blogs or reddit and refine my expertise. Whether it’s improving processes, solving data challenges, or visualizing insights, I am always excited to tackle the next problem.

• 🖥️ Languages: Proficient in R, Python (including seaborn, shap, matplotlib, and other typical libraries), SQL (MS SQL Server, PostgreSQL, MySQL), and Bash.
• 🛠️ Version Control: Expertise with GitHub, GitLab, and MS DevOps (pipelines and workflows).
• 📊 Data Visualization: Experienced with Power BI, Qlik Sense, Grafana, and libraries like ggplot2, seaborn, and matplotlib.
• ☁️ Cloud Platforms: Skilled in Azure, GCP, and AWS.

• 📂 Data Pipelines: Proficient with Apache Airflow, pipeline automation via MS DevOps and GitHub.
• 🔗 APIs: Extensive experience with RESTful APIs (import/export).
• 🛠️ Big Data: Knowledge of Hadoop and data engineering frameworks.

• 🔍 Machine Learning: Comprehensive expertise from regression to advanced techniques:
  • Supervised & Unsupervised Learning
  • Deep Learning with TensorFlow and PyTorch
  • Grid Hyperparameter Tuning, SHAP for interpretability
  • Explorative & Predictive Modeling
• 🧠 Large Language Models (LLMs): Hands-on experience with Ollama, HuggingFace Transformers for text generation, text-to-image, image-to-text, and voice-to-text.
• 📈 Time Series Analysis: Extensive experience with forecasting tools like Prophet, change-point detection, and advanced techniques.
• 🔢 Optimization: Expertise in linear programming with lpsolveapi for applications like resource optimization, cost reduction, and sample selection.
• 🔍 Predictive Maintenance: Exploring sound and ultrasound analysis (e.g., Frugatto).

• ✅ Quality Assurance: Significant experience with:
  • Outlier Detection, Completeness Checks
  • Trustworthiness Evaluation, Fraud Detection
  • Duplicate Identification and mitigation

• 📜 Reporting: Skilled in JAMstack, shiny apps, markdown, and dockerized environments.
• 🚀 Model Deployment: Experience with Flask and serving machine learning models in production.

• 👁️ Vision Applications: Expertise with OpenCV for various computer vision tasks.

• 🌟 Open Source Contributions: Active on GitHub, TidyTuesday, and StackOverflow.
• 👩‍🏫 Teaching and Mentorship: Mentored PhD students and contributed to skill development.

• 💬 Passionate about exploratory data mining, data visualization, and gamification.
• 🎮 Interested in board games, video games, and scrapping data about them on a lot of platforms.
• 🧗 Enjoys badminton, climbing, and aquaponics.