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Web software engineer

Considering positions:
Web software engineer, Java software engineer, PHP Software Engineer, UI Software Engineer
City of residence:
Kyiv
Ready to work:
Remote

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Nataliia Shvorak
[open contact info](look above in the "contact info" section)

[open contact info](look above in the "contact info" section)

6 Blinshall street, Dundee, DD1 5DS

LinkedIn GitHub

Personal Profile
Motivated and detail-oriented fourth year Computing Science student
with a solid foundation in software development and object-oriented
programming developed through academic coursework and
collaborative projects. Seeking a software engineering role where I can
apply my technical knowledge and problem-solving skills to develop
advanced, real-world applications.

Education
September 2022 – June 2026, University of Dundee | BSc
Computing Science, 2:1 predicted

Key modules: Networks and Data Communications, Database Systems,
Mobile Application Development, Agile Software Engineering, Object
Oriented Analysis, Machine Learning, Data Visualization Analytics,
Computer Systems

2018 - 2022, Kyiv natural Sciences Lyceum 145

Technical skills
• Programming Languages: HTML, CSS, JavaScript, Java,
Python, C++, SQL
• Libraries and frameworks: React.js, Node.js, Flutter, Scikit-
learn, TensorFlow
• Tools: Microsoft Office 365, VS Code, Firebase, Git, GitHub
Jupyter Notebook, Wireshark, AWS
• Deep understanding of and experience with machine
learning algorithms: k-means clustering, decision trees,
linear and logistic regression, neural networks

Projects
• Operation Scheduler: developed a JavaFX application in a team of
three to schedule doctor appointments. Implemented appointment
management features, allowing users to create, update, delete and
view bookings.
• ATM Simulator: Collaborated in a university group project using
Agile sprints to design an ATM system. Contributed to the
implementation of the Transaction Switch part of the project and
participated in sprint planning and iterative development.
• Cyclones analysis: implemented machine learning algorithms,
such as Multi-Layer Perceptron and Random Forest to classify
tropical cyclones from Hurricanes and Typhoons 1851-2014
dataset with 90% accuracy

Additional information
• Participated in two Hackathons organized University of Dundee
Computing society
• Participated and received awards in math and physics
competitions in high schools
• Served as an event manager in Ukrainian society
• Languages: English, Ukrainian(native), German(beginner)

References
Available on request

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