Javascript Developer & Node.js Developer & React Developer

The candidate is a fullstack developer/engineer who works primarily with Node.js, which he has over a year of commercial experience with, but worked with part-time for four years during school. On his last project, he was developing taxi management software. Each car had a GPS device that sent information about location, mileage, etc. and could be tracked live. Among the technologies there, he used Node.js, React, Typescript, MongoDB, PostgreSQL. Apart from Node.js, he also knows machine learning, data science, can work with neural networks, knows data analytics, Javascript, Docker, Python, Flask, Jupyter. In the future, he would like to focus on Backend development. He speaks English at B2 level and expects to communicate in English on projects. He has experience with agile methodologies and has no problem using them.

Full Stack Software Engineer (05/2017 - 06/2022): Developed web applications in the transport and taxi domain, along with side projects based on customer requirements. Utilized technologies such as Node.js, React, TypeScript, MongoDB, PostgreSQL, Redis, Jupyter, Kubernetes, and Docker. Worked on a team of 5 developers.

Full Stack Developer (09/2019 - 05/2020): Developed an AI chart recommender system in data analytics and presentation online web tool. Implemented a machine learning model accessible via REST API. Collaborated with Instarea on a year-long school project. Used Python, Docker, ML, Flask, and Jupyter. Worked on a team of 5 developers.

Engineer (2019 - 06/2021): Completed a thesis on deep neural networks for information retrieval from medical image data. Specialized in segmentation using deep learning methods in the domain of medical image data, specifically organs at risk in CT scans. Proposed and evaluated a multi-step segmentation method using two neural networks. Worked on a team of 3 developers.

Bachelor (2016 - 2019): Conducted research on personalized recommendation systems in the domain of interesting places using the Yelp public dataset. Proposed a method based on collaborative filtering with ML clustering by business features to reduce rating sparsity. Worked on a team of 3 developers.

High School Diploma (2008 - 2016): Graduated from Gymnázium Antona Bernoláka v Námestove.

Language Skills: Slovak (Native), Other Language Skills: English (C1).

Digital Skills: Restful API, JavaScript ES6/TypeScript, Web Development, Linux, Git, Node.js, React.js, Docker & Kubernetes, NoSQL (MongoDB), Microsoft Office, CSS, Recommender Systems, Bootstrap, Data Science, Deep Learning, JSON, Software Engineering, Python, SQL, Machine Learning, HTML, Programming, JavaScript.