Особисті дані приховані

Vlad Slabidker
Nationality: Ukrainian Date of birth: 05/08/2004 Place of birth: Odesa, Ukraine

Gender: Male  Phone number: [відкрити контакти](див. вище в блоці «контактна інформація»)

 Email address: [відкрити контакти](див. вище в блоці «контактна інформація»)
 Telegram: @slabidker
 Website: https://github.com/VladSlabidker/BRCBot
 Website: https://github.com/VladSl4

EDUCATION AND TRAINING

Bachelor`s degree
Odesa National Mechnikov University [ 01/09/2023 – Current ]
City: Odesa | Country: Ukraine | Field(s) of study: Applied Mathematics

Comprehensive program focused on advanced mathematics, statistics, and computer science with strong emphasis
on problem-solving, mathematical modeling, and programming. Core studies included:
• Calculus I, II, III, Linear Algebra, Probability Theory & Statistics
• Numerical Methods, Optimization, Differential Equations, Functional Analysis
• Algorithms, Data Structures, and Computational Methods
• Mathematical Modeling in Physics, Engineering, Economics and all fields
• Programming (Python, C++, Java), Data Analytics, Software Engineering, Machine Learning, Deep Learning
I am a highly motivated and fast-learning specialist with the ability to quickly adapt to new technologies, frameworks,
and areas of knowledge. Throughout my studies in Applied Mathematics, I successfully combined intensive training
in advanced mathematics with hands-on programming experience, which allowed me to develop a unique balance
between theoretical thinking and practical problemsolving. I have demonstrated the capability to rapidly absorb
complex concepts and apply them in practice, whether it involves mathematical modeling, algorithm design, or
software development. This adaptability enables me to contribute effectively in interdisciplinary environments,
where strong analytical skills, programming expertise, abstract thinking and the ability to learn on the fly are
essential.
The main focus of my education is applying strong mathematical concepts to real world problems. I chose the ML\DL
way of applying my knowledge, because, in my opinian, the AI technology is the one, that will be driving the
improvement of all the aspects of living drastically.

DESIRED GROWTH

Machine Learning Engineer \ Data Scientist

I am proficient in Python and have strong mathematical background. Due to my education, I have accuired solid
theoretical knowldege and some practical skills in Machine Learning and Deep Learning, using PyTorch and scikit-
learn. I am eager to grow professionaly in this sphere and really looking forward to grasping new opportunities of
becoming a Machine Learning specialist and learning from professionals, who are willing to help me achieve my
dreams.

WORK EXPERIENCE

 Ornament-Soft Solutions – Remote

C#/.NET Software Engineer
[ 19/09/2024 – Current ]
Worked on the development of enterprise-grade banking software within a microservices architecture, focusing on
reliability, scalability, and compliance with strict financial standards. Responsibilities included:
• Designed and implemented backend services using C#/.NET (ASP.NET Core, Entity Framework Core, LINQ) and
SQL, applying Clean Code, DI, MVC, SOLID, DRY, KISS, YAGNI principles.
 • Developed and maintained inter-service communication using REST, gRPC, and RabbitMQ, ensuring fault-
tolerant and high-throughput messaging.
• Applied Redis for caching and performance optimization of critical banking operations.
• OpenAPI/Swagger documentation
• Participated in CI/CD pipelines, implementing unit tests and smoke tests to ensure quality, security, and
stability of releases, using Git VCS and GitLab CI
• Collaborated in architectural decision-making, including service design, modularization, and selection of
design patterns for long-term maintainability.
• Implementing Unit-testing using NUnit framework.

SKILLS

Python / Machine Learning / Deep Learning / PyTorch / Scikit-learn / Pandas / NumPy / C#/.NET(ASP. NET
Core) / SQL (MS SQL Server) / NoSQL(Redis) / Entity Framework Core / gRPC / REST / RabbitMQ / Git

LANGUAGE SKILLS

Mother tongue(s): Ukrainian

Other language(s):
English German
LISTENING C1 READING C1 WRITING C1 LISTENING C1 READING C1 WRITING C1
SPOKEN PRODUCTION C1 SPOKEN INTERACTION C1 SPOKEN PRODUCTION C1 SPOKEN INTERACTION C1

Levels: A1 and A2: Basic user; B1 and B2: Independent user; C1 and C2: Proficient user

CERTIFICATIONS

[ 03/2023 ]
telc C1 Hochschule German

[ 04/2022 ]
DuoLinguo English Exam (Grade 135: C1+) English

[ 08/2021 ]
FCE Cambridge Certificate (Grade A: C1) English