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purple-papaya/README.md

Pavlína Nováková

Data Analyst · Industrial Devices · Predictive Maintenance

Transforming complex data into actionable insights

LinkedIn Email Location

About Me

I build data pipelines for high-end biomedical devices that help maintenance professionals make better decisions before equipment fails. My work focuses on improving switch rates—the metric showing how many pipeline-generated alerts experts consider valid and act upon.

My path to data analytics started in neuroscience research, where I analyzed EEG patterns and studied how cannabinoids and psychedelics affect brain activity. That foundation taught me to extract meaningful stories from complex, messy data - a skill I now apply to predictive maintenance at scale.

Beyond the technical work, I've spent years translating clinical and pre-clinical scientific literature, which sharpened my ability to communicate complex findings to both data scientists and stakeholders who need the bottom line.

Tech Stack

Languages & Libraries

Python SQL Pandas NumPy

Platforms & Tools

Databricks Jupyter Git GitHub Actions

Visualization

Plotly Matplotlib

Domain Expertise

Biomedical Predictive Maintenance Healthcare Neuroscience

Professional Journey

2024-Present  Data Analyst           Datamole    │ Biomedical pipelines & Databricks migration
2019-2021     Medior Data Analyst    Datamole    │ Algorithm review & stakeholder communication  
2018-2019     Data Analyst           Datamole    │ Pipeline development & data visualization
2015-2021     Expert Translator      Self-Employed │ Clinical literature & data monitoring
2013-2014     Research Scientist     NUDZ        │ EEG analysis & neuroscience research

Education & Certifications

🎓 Master's Degree — Animal Physiology · Charles University, Prague

🎓 Bachelor's Degree — Molecular Biology and Biochemistry · Charles University, Prague

Certifications

ML CAE Digital

What I'm Currently Working On

  • 🔄 Collaborating on Databricks migration for biomedical data pipelines
  • 📈 Improving predictive maintenance algorithms to increase switch rates
  • 🛠️ Building CI/CD workflows for development automation
  • 📚 Exploring advanced time-series analysis techniques for device monitoring

Let's Connect

I'm interested in connecting with others working at the intersection of data science, healthcare, and biomedical innovation.

Whether you're working on predictive maintenance, healthcare analytics, or just want to chat about turning messy real-world data into actionable insights—let's talk.

LinkedIn Email

"The goal is to turn data into information, and information into insight." — Carly Fiorina

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