I am Muhammet Fatih Çetintaş. I work at the intersection of software development, applied AI, data analytics and systems integration. I care about understanding the data, process and technical boundaries behind a problem, as well as its interface.
My work ranges from local language-model experiments and document processing to financial records and healthcare research tools. Experience with enterprise systems shapes the way I examine how a technical solution fits its real operating context.
I distinguish experiments, prototypes and validated outcomes. Explaining architecture, protecting data and describing the limits of testing are part of how I build.
Software, infrastructure, application support and integration experience inform a systems-level approach to problem solving.
04/2026 — Present
Optimak STU / Logirobotic
Autonomous Systems and Software Applications Specialist
Software applications, enterprise integration and technical validation.
Responsibilities and technical context
I translate operator actions, task lifecycles and business rules in production and warehouse logistics into technical requirements and test scenarios. I contribute to validating REST/JSON communication, MES integration flows, timeouts and task/feedback consistency, and support field teams through technical documentation, user training and acceptance checks.
API analysis · Systems integration · Technical validation
06/2025 — 11/2025
Private Medar Hospital
IT Specialist
Enterprise infrastructure, healthcare information systems and technical troubleshooting.
Responsibilities and technical context
Supported access and operational continuity for Medisoft HIS and Sonitel PACS in a hospital with over 140 client devices. Worked on troubleshooting Windows Server 2022, Active Directory, Hyper-V (four VMs), SQL Server and VPN services, and analyzed laboratory RS-232/COM and printer integrations while developing Python helper tools.
Windows Server · Active Directory · Hyper-V · SQL Server · HIS/PACS
10/2024 — 06/2025
Independent work
Software and AI development
Report processing, data analytics and research software.
Responsibilities and technical context
Extracted and cleaned data from approximately 400 Tanita reports and contributed to a 395-patient analysis dataset. Linked clinical variables, anthropometric measurements and questionnaires with Python/pandas, and worked on classification and model evaluation. Developed signal-processing and feature-extraction prototypes for EEG-based yes/no communication research.
Python · Data processing · Machine learning
11/2024 — 03/2025
Gini Talent
Search result evaluation and quality analysis
Relevance and quality evaluation of search engine results.
Responsibilities and technical context
Evaluated search results against guidelines for user intent, relevance and content quality. Contributed to data annotation, quality control and review of result consistency.
Quality evaluation · Analytical review
07/2024 — 11/2024
MKU Teknoloji / RAITOY
Software development intern
Internship experience in software development processes.
Responsibilities and technical context
Provided technical support for Python development, data preparation, application testing and error analysis in AI, web and mobile software work.
Software development · Team collaboration
02 / EDUCATION
Education
Bachelor’s degree
Management Information Systems
Ahmet Yesevi University
2026 — Present · Distance learning
Bachelor’s degree
Economics
Anadolu University
2026 — Present · Third year
Associate degree
Computer Programming
Bartın University
2022–2024 · Graduated · GPA 2.78/4.00
High school
Motor Vehicle Technology
Arifiye SATSO Vocational and Technical Anatolian High School
In sleep-apnea research associated with Sakarya University Faculty of Medicine, I extracted and cleaned data from approximately 400 Tanita reports and contributed to a structured analysis dataset covering 395 patients. I worked with anthropometric measurements, clinical variables, AHI/OSAS classes and questionnaire results for data processing and model evaluation. My EEG/ALS work involved signal processing and machine-learning prototypes for yes/no intent classification. These remain research activities.
