Meric Ozcan
I gained 3 years of domestic and international e-commerce and digital marketing experience in my own venture. While trying to improve sales performance using my business's data, I realized my passion for statistics and data analysis.
In the data analysis process, I have a good level of competence in the Problem Definition, Data Collection, Data Discovery (EDA) and Results Interpretation stages; an intermediate level in the Data Cleaning, Data Visualization and Reporting - Presentation stages; and an entry level in the Data Manipulation - Preparation, Data Analysis - Modeling and Development - Improvement stages.
I am a member of the best societies in my university and in Izmir. I have been on the board of directors of GencKalder Izmir since 11.2024 and I both take part in and carry out academic and technical projects.
I have B2+ English proficiency.
I plan to learn German or French in the future.
I am currently interested in data analysis and data analytics.
I am interested in finance, inspection and analytics departments in the banking sector.
After gaining sufficient experience in my career, I aim to develop a venture that provides SaaS services in the field of fraud detection.
PROFESSIONAL EXPERIENCE
Banking Internship
QNB Turkey
Istanbul
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Activities: Advanced Excel · Problem Solving · Presentation Techniques
01.2025 - 02.2025
Business Founder
Izmir
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Activities: Management · Financial Planning · Business Process & Strategic Planning
05.2021 - 05.2024
07.2020 - 08.2020
EDUCATION
Ege University
Bachelor's Degree in Statistics
Izmır, Turkey
09.2022 - 06.2027
Artificial Intelligence and Technology Academy
Google Advanced Data Analytics, Google Project Management and Entrepreneurship Trainings
01.2025 - 08.2025
PROJECT EXPERIENCE
TÜBİTAK 2209-A | Project Manager
Optimization of Safe Delivery of Cargoes with Artificial Intelligence
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Conducting quantitative research on logistics risk analysis and management for international maritime deliveries
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Designing a web-based system that provides autonomous logistics risk and satisfaction reports using AI
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Creating a data analysis and forecasting platform that predicts e-commerce customer satisfaction and shipping risks by analyzing open-source customer reviews.
FraudShield: Real-Time Transaction Risk Scoring System
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This project analyzes credit card transactions in real time and provides users with a risk score between 0–100.
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A user-friendly Streamlit interface visualizes the score and instantly reports low, medium, and high risk levels.
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By using statistical methods, machine learning, and imbalanced data techniques such as SMOTE, the reliability of transactions is measured, enabling a more robust evaluation of system performance and decision-making.
Shell Eco Marathon Hydrogen Fuel Electric City Vehicle Competition Category Project Team
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Conducted multi-criteria parameter optimization studies for hydrogen-powered electric vehicles.
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Focused on weight, cost, and energy efficiency analyses to enhance performance and competitiveness.
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Integrated machine learning-based algorithms and mathematical modeling techniques to improve the reliability of results.
SKILLS AND EXPERIENCE
Statistics
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Data Analysis
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Data Analytics
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Statistical Research
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Data Visualization and Reporting
Technical Skills
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Python
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SQL
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Excel
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Power BI
Soft Skills
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Project Management
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Crisis Management
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Effective Presentation
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Analytical and Creative Thinking







