Dimitrios Diamantidis

Project-based role with DataStudent supporting the Instituut voor Zorgoptimalisatie (INSZO) in modernizing their data infrastructure. Migrated legacy SAS data science scripts to SparkR within Azure Synapse Analytics, delivering the project successfully.

• Translated complex SAS workflows, including data imputation, feature engineering, and statistical modeling (regression, clustering, classification) into SparkR and SQL, ensuring reproducibility and accuracy across platforms.

• Leveraged SparkR/Pyspark and SQL to efficiently manage and transform large-scale healthcare datasets in a cloud-based environment, optimizing scripts for performance and scalability.

· Collaborated closely with INSZO's Data Science team to validate methodologies and align transformation logic with clinical and research objectives.

. Gained valuable expertise in the comparative use of statistical functions and data operations across programming languages, with a focus on healthcare data applications.

• Build real-time data solutions that improve automation, streamline data collection, and deliver actionable insights tailored to client needs.

· Specialize in data extraction and automation, utilizing Python (Selenium, Playwright, BeautifulSoup) and APIs for both dynamic and static web scraping.

. Optimized data workflows and developed automated data extraction solutions for a procurement platform.

. Enhanced data clarity using Python and deep learning (CNN) to clean and standardize data for analysis.

. Build an email scraper with Python (Pandas, BeautifulSoup, nltk, Regex) to automate vendor offer consolidation, transforming unstructured data into actionable insights.