Денис

Experience
Trainee Data Analyst (Dec 2022 – Mar 2023)
I worked as a Trainee Data Analyst for 4 months. Was
responsible for data clearing, manipulating and analyzing. In my
work I used SQL (SQL Server Management Studio), Excel and
Alteryx.

Pet Projects
 Analyzing and applying OpenCV object tracking algorithms
(GitHub)
Denys o I created a project to automate the routine task
(fishing) in the computer game Minecraft using
Hryhoruk 
Python and the OpenCV library.
Website for task management (GitHub)
o The purpose for creating this project is adding,
Trainee Data Scientist monitoring and achieving your daily goals. It was
developed using Django, SQLite and JQuery.
Ukraine, Lviv  Gmail Drafter (GitHub)
o This small project uses Google API to draft emails in
[open contact info](look above in the "contact info" section)
your Gmail account.
[open contact info](look above in the "contact info" section)  Project “StrongNation”
o With a team of students, we did a Telegram bot,
which was created to support Ukrainians with helpful
Skills and interesting information in wartime.
o I was responsible for the code part (Python), data
Calculus: gathering and server part.
Linear Algebra: Education
Probability Theory: Ivan Franko National University of Lviv
Optimization Theory:
Statistics:
Computer Science
Algorithms and data (2021-nowadays)
structures: I did (and do) a lot of labs about data structures (doubly linked
Python: list, stack and queue via linear lists), OOP (with C++), discrete
mathematics (combinatorics, trees), algorithms (bubble,
SQL: insertion and selection sort, BFS, DFS, Dijkstra and Floyd
Optimization Theory algorithms), some optimization theory and Linux OS.
L:
English: Upper Intermediate (B2) I learn Math a lot at university and continue to learn more.
I am a person, who has Math
thinking, strong time
management, responsibility,
Professional Development
team-working, communication,
has a great desire to learn new
Achievements
technologies and a desire to I’ve done a lot of mini projects implementing machine learning
become a data scientist. models such as linear regression (linear, logistic, polynomial),
classification (SGD, Naive Bayes, SVM) and clusterization (K-
means). I enjoy data gathering, clearing and analyzing it.