Researchable·Groningen, Netherlands
Data Science Intern
·internship
Built data pipelines and ML models for an academic analytics platform, working on research impact metrics and trend analysis.
- ▸Designed and implemented ETL pipelines processing academic publication data
- ▸Built ML models for research impact prediction and topic trend analysis
- ▸Worked with large-scale bibliometric datasets (millions of publications)
- ▸Delivered production-ready data processing components integrated into the platform
Technologies
PythonPandasScikit-learnPostgreSQLDocker
Context
Researchable is a Groningen-based company building analytics tools for the academic research sector. I interned as a data scientist, working on their core data processing and analysis infrastructure.
What I Did
- Built ETL pipelines for ingesting and processing academic publication metadata
- Developed ML models for predicting research impact and identifying trending topics
- Worked with PostgreSQL databases containing millions of publication records
- Created data visualization dashboards for internal stakeholders
Impact
Delivered production-ready pipeline components and ML models integrated into the platform.
What I Learned
- Practical data engineering skills — handling messy, real-world data at scale
- The gap between Jupyter notebook prototypes and production-ready code
- Working with domain experts (bibliometrics researchers) to translate business needs into technical solutions