Position: Data Analyst
Category: Data Analyst
English level: fluent
Years of experience: 1.5

Saw opportunities for improvement and proposed more efficient solutions and implemented many automations for processes, that previously were done manually. Most interesting case was regarding automation of interviews' transcripts preprocessing. I wrote a script that iteratively read each transcript, chose relevant parts and wrote it automatically to the appropriate word file. (saved about 2 human hours for each interview). Used simple NLP - matching questions via stemming and Levenshtein distance.
- Data collection: web scrapping, extraction via API from social media.
- Data cleaning and processing, EDA, ETL pipeline.
- Data analysis (hypothesis testing, a/b testing, confidence intervals, correlations, frequency tables, aggregations, respondents segmentation, linear regressions) Making visualisations and interactive dashboards (python matplotlib, Tableau).
- Misc. : created and managed a database of mobile phone numbers that came from raw collected data (RegEx), coded interview questionnaires (KOBO form), managed tracking of the data collection process with google sheets, conducted technical workshops, wrote documentation for scripts (Python and R).

Data Science Master’s Program, UCU [2020-2023]

- Understanding of fundamentals of Linear Algebra, Probability theory, Statistics, Calculus.
- Knowledge and application of classic machine learning algorithms. Ability to read, understand and prototype ideas from academic papers.
- Ability to quickly understand task, research best recognised practices, try several of them, compare results and choose the best one under existing conditions.
- Various learning projects. To name a few: prediction of car prices, recognition of person's movements from gyroscope data, building a recommender system, calculation of "fraudulence" score for politicians based on open declarations, 3D reconstruction, object detection.
I would like to avoid using old and manual ways of doing things (where possible) - I am interested in automating and making more efficient solutions (also where possible).