Katharine Jarmul
Privacy Specialist at kjamistan
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolKatharine Jarmul is a privacy specialist and data scientist with 15 years of experience building privacy-first data platforms, advising organizations, and delivering trainings and workshops. She has held leadership roles from Principal Data Scientist at Thoughtworks to founder and product lead positions at privacy startups like KIProtect and Cape Privacy, shaping encrypted learning and anonymization products. Katharine combines hands-on data engineering and cleaning expertise—evidenced by substantial contributions to data-wrangling and data-cleaning Python repositories—with strategic guidance on governance, compliance and privacy-aware AI implementations. Based in Berlin, she helps teams embed privacy into AI/ML lifecycles and has developed novel privacy technology implementations tailored to real-time analytics. Beyond technical delivery, she creates learning material and mentors practitioners to scale privacy understanding across distributed systems like Data Mesh. A former journalist and early NLP engineer, she brings a pragmatic, communication-first approach to translating complex privacy tradeoffs into actionable product decisions.
15 years of coding experience
13 years of employment as a software developer
M.A., Media - Public Policy, M.A., Media - Public Policy at American UniversityM.S., Education, M.S., Education at Pace University
English, German
Github Skills (13)
data-wrangling10
pandas10
jupyter-notebook10
data-validation10
data-cleaning10
python10
csv9
data-analysis8
scikit8
pdf-parsing8
scikit-learn8
sql7
sqlite7
Programming languages (9)
Github contributions (5)
kjam/data-cleaning-101
May 2017 - May 2018
Data Cleaning Libraries with Python
Role in this project:
Data Scientist
Data ScientistContributions:10 commits, 1 PR, 11 pushes in 1 year
Contributions summary:Katharine contributed to data cleaning and validation tasks within a data science project. They modified existing notebooks, likely to incorporate changes for new datasets or resolve issues. The contributions focused on data manipulation, cleaning, and validation using Python libraries like Pandas, and integration with SQL databases. Additionally, the user demonstrated an understanding of data preprocessing and feature engineering techniques.
data-cleaningpythonteachingdata-validationdata-wrangling
jackiekazil/data-wrangling
Aug 2015 - Feb 2017
Code repository for Data Wrangling with Python (O'Reilly)
Role in this project:Data Scientist
Data ScientistContributions:23 commits, 1 PR, 23 pushes in 1 year 6 months
Contributions summary:Katharine primarily contributed to the data wrangling repository by updating data files and organizing files for different chapters of a book. They added and modified code related to cleaning and processing data from various sources, including HTML files and CSV files, specifically focusing on life expectancy and child labor data. The commits indicate a focus on data cleaning, transformation, and potential integration with a database (SQLite) for analysis and exploration. The user also demonstrated the ability to process data from different file types, including Excel and PDFs using appropriate libraries such as `xlrd` and `pdftables`.
data-wranglingpython
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