Position: Data Analyst/Data Scientist/Machine Learning Engineer
Category: Data Science
English level: fluent
Years of experience: 2

I have achieved significant accomplishments in various professional competitions and certification programs, highlighting my expertise and contributions in the field.

Firstly, I was recognized as a finalist for the Texnofest Certificate in Social Technology, where I served as the team leader. This certificate attests to my proficiency in utilizing technology for social impact and demonstrates my leadership abilities in guiding a team towards success.

Additionally, I secured the second place in the Socar Hackaton competition, showcasing my skills as a machine learning engineer. Through this competition, I demonstrated my ability to develop innovative solutions using machine learning techniques and contributed to a high-ranking project.

Furthermore, I participated in the Pasha Hackaton competition, where my performance earned me the distinction of being a finalist. This experience allowed me to showcase my problem-solving capabilities and collaborate effectively with a team in a time-constrained environment.

Moreover, I have obtained a Khan Academy certificate for my contributions in translating mathematical content from English to Azerbaijani. This certification verifies my language proficiency and showcases my commitment to making educational resources accessible to a wider audience.

These achievements highlight my dedication to continuous learning, innovation, and contributing positively to the professional community. I am excited to leverage these experiences and skills to make significant contributions to future endeavors in the field of technology and data analysis.
I have gained valuable professional experience in various roles within the field of data analysis and data science. I have held a position as credit risk modelling at Kapital Bank, the largest bank in Azerbaijan, for a duration of 
8 months. During this time, I contributed to the development and implementation of credit risk models.

Prior to my job, I served as a data scientist in a FemTech startup, where I was a member of the Tech Team for 7 months. My primary focus was on leveraging natural machine learning techniques for tasks such as feedback analysis, customer segmentation, and the application of various machine-learning algorithms. To enhance the accessibility of the results, I utilized Python as my programming language of choice and employed PowerBI to generate insightful and user-friendly dashboards.

Furthermore, I have gained experience as a Data Analyst intern at both 166 Freight and Logistics companies and QSS Analytics companies, where I worked for 5 and 4 months, respectively. In these roles, I utilized Python for tasks such as web scraping, customer segmentation, sentiment analysis, and RFM analysis. These experiences have equipped me with a diverse skill set and a comprehensive understanding of data analysis methodologies.

Lastly, I have also dedicated 10 months to teaching as a Python instructor at GI GROUP. This teaching experience has allowed me to effectively communicate complex concepts to students and foster their understanding of Python programming.

Overall, my professional background encompasses a range of roles within the data analysis and data science domains. I have demonstrated proficiency in utilizing Python, NLP techniques, machine learning algorithms, and visualization tools such as PowerBI to deliver impactful results. I am confident in my ability to contribute effectively to future projects and organizations within the field.
My desire is to become a part of a team that is working on diverse and challenging projects. It is important for me to work alongside team members who have varying levels of experience so that I can both contribute my knowledge and learn from others.