Position: Data Analyst
Category: Data Science
Experience: 1.5 years | English: fluent

First of all, I have been teaching Mathematics and English since 2014. I know my way around people of different cultures and backgrounds and can easily explain things that people don’t understand. My background in Further Mathematics improved analytical vision and problem solving tactics I use to this day. Moreover, throughout the years of my work I developed strong stress management skills that allow me to stay with a cool head even at some crazy moments.
Throughout my studies I encountered a lot of different programming languages, that gave me a skill of adaptability, that allows me to be on the ball even if something completely new is presented to me. At last, I am a team player, who organized all my group works by collecting the team and evaluating our skills for the achievement of the given task. I am happy to work with others in a team. However, I am also self-sustainable and can produce quality work on my own without supervision.
I have worked as a Junior Plus Data Scientist for a year already. I had a vast experience in Planning and creating Jupyter Notebook scripts that allowed me to automatize the processes of creating reports from advertisement data (collected from Big Data Query) that were previously done by hand. This approach allowed the company that I worked for to save a lot of time and become far more efficient in the department that I worked. I was responsible for the optimization of internal processes as well. In particular, I was promoting the idea of using scripts to save time and resources of my colleagues. To do that I created detailed guides that provided insight into how the script works and how to operate it on the basic level. Throughout this experience, I have gained confident knowledge of NumPy and Pandas and I believe I have the qualities to shape the data of any shape or form. 

During the Data Science course, we went through python, NumPy, Pandas, power bi and seaborn visualization.  We also studied machine learning using scikit-learn on a project to predict apartment prices in Kyiv using ensemble (Logistic regression, random forest classifier, xgb classifier, decision tree classifier and voting classifier). We also looked at unsupervised learning in the form of association rules using apriori. The final data science project for me was in the form of an analysis of the company's sales, including customers, products ABCXYZ analysis, and the time when orders were placed.

 At the university, I took a course in Artificial Intelligence, where I studied Neural Networks through matlab, created a neural network that could distinguish handwritten numbers. Autonomous systems taught how to program the actions of the NAO robot through python. It was able to get up from a supine position, find balance, and ultimately be able to stand on one leg. At the end of this subject, my robot could identify the ball and the goal, walk up to the ball and score a goal without falling. Many other projects were made and implemented (knowledge base system to assist on workouts for people with various age/health conditions in python, ACT-R human response simulation of a monotonous experiment involving daydreaming and so on).