Tacdin Ozmen
I’m Tacdin Ozmen, a healthcare-focused Data Analyst based in Switzerland with a BSc in Nursing and strong analytics training through the IBM Data Science and Data Science Professional Certificates.
About
I’m Tacdin Ozmen, a healthcare-focused Data Analyst based in Switzerland with a BSc in Nursing and strong analytics training through the IBM Data Science and Data Science Professional Certificates. Over the past five years, I’ve supported Ministry of Health operations by auditing high-volume clinical and billing records, building validation logic to improve documentation quality, and turning complex healthcare data into clear, action-oriented reporting.
- 4 years' experience
- Joined November 2026
Languages
- TurkishFluent
- KurdishFluent
- ItalianFluent
- EnglishAdvanced
- GermanAdvanced
Industry experience
- Healthcare
- Government
- Life Sciences
- Professional Services
Work experience
Audited daily hospital operational and billing workflows across Hospital Information Systems (Panates, Fonet), validating ~1,000 invoices/day for accuracy and regulatory compliance. Built rule-based validation checkpoints to ensure required treatments align with documentation records for ~20 system users. Reduced incomplete entries and billing error rates from 90% to 10% by enforcing mandatory fields, standardizing data-entry logic, and streamlining operational workflows. Automated data-quality monitoring and delivered targeted training to 100+ healthcare and administrative staff, contributing to a 275% revenue expansion (3.75x) over 18 months. Produced ad-hoc operational schedules and management reporting using MS Excel and SQL for service volumes and resource allocation.
Audited high-volume daily healthcare records and medical billing workflows (~1,000 invoices/day) across Hospital Information Systems (Panates and Fonet), ensuring data accuracy and compliance with health regulations. Engineered rule-based clinical validation checkpoints for ~20 system users, linking required medical treatments to documentation records to reduce reporting errors and support data governance. Reduced incomplete entries and clinical billing error rates from 90% to 10% via standardized data-entry logic, mandatory field enforcement, and streamlined operational workflows. Improved institutional revenue 3.75x (275%) over 18 months by automating data quality monitoring and delivering targeted training to 100+ healthcare and administrative staff. Built operational schedules and management reports using MS Excel and SQL for clinical department heads and executives.
Education· 8
Certifications and awards· 6
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