Fintech Software Engineer- Developed and optimized REST API endpoints using actix, serde and some other popular Rust crates.- Decreased memory use by 20-30% by decreasing the unnecessary clones and object transfer between functions.- Improved existing endpoints response times by 10-20% by optimizing existing logics and algorithms without losing the functionality.- Integrated GitHub hooks for streamlined version control and decreased code review time by 20-30%.- Contributed to the development and improvement of a complex gateway system connecting multiple banks and insurance companies, enhancing efficiency in processing insurance offers.- Collaborated on the enhancement of the authorization system to ensure secure access for multiple banks while maintaining data privacy.- Proficiently worked in a Dockerized environment, demonstrating expertise in containerization for streamlined deployment and enhanced scalability.

I took part in the development of microservices of the A101 Kapida e-commerce application using rio services, typescript and node.js• I have integrated the system with Qdelivery courier application.• Since the rio services run on AWS, I gained basic competence in AWS services such as lambda, S3 dynamo and IAM.

After a one-month of internship (6 September - 1 October), I have worked as a candidate engineer.• I have learned the basics of AI and Deep Learning.• For AI model training we have obtained more than 100.000 of thermal and RGB images from the healthy, rotten and diseased plants from greenhouses at Antalya and Ankara and labeled them.• We have trained Deep Learning models using YOLO v3 to differentiate crops from the leaves and landscape and determine their harvest status.• We have obtained 3 models with >90% accuracy and >0.9 f1 score. Training set and test set have been seperated by 80% - 20% for each model. (3 models are respectively for tomato, lettuce and pepper)• Using OpenCV library, I developed an algorithm that calculates the dimensions of unknown objects using stereo images with an accuracy of over 90% for harvest forecast.• I have developed code to plot the data from 40 sensors with less than 200ms delay within the local connection. (20 temperature and 20 moisture sensors placed evenly to check the environment conditions in greenhouse for the crops).• Using the image processing on thermal and RGB images we have tried to detect diseased plants before the symptoms appeared. We have detected only some specific diseases up to 2 days before the symptoms appeared.

• I have made simulations in Simulink for Pulse Width Modulator(PWM) for DC to AC converter.• I have developed code that converts Excel files with more than 1 million lines of data to the desired format using pandas and numpy with Python.

The PEP Online, which I attended during the Covid-19 pandemic period, I have learned the working structure of different departments in Mercedes-Benz and the culture of the company.• My team have suggested the best solution among the 7 teams in the case study I have participated in. The study was determining the best country for Mercedes-Benz to build new factory for given conditions.

• I have attended 3 face-to-face sales visits.• With Excel VBA, I have written 2 separate applications 1-) Application to record product revision. The application is used to record the id and revised properties of the product. 2-) Application to record the faulty production. The application is used to record the production line responsible for faulty production and the time of fault.

In the N-Sid-Sen camp, I have served the groups mainly consisting of the elderly and children. In this process, I have had the opportunity to learn American culture and I have also improved my fluent communication skills in English. The problems we have faced allowed me to improve my teamwork and crisis management skills.