Position: Product Analyst
Category: Data Science
English level: fluent
Years of experience: 4

• I am a participant in different kinds of hackathons and programming competitions (Google Hash Code, ICPC)
• Representative of my university at a national research science competition in the economic cybernetics department.
• I am an active member & organizer of local communities and conferences (Product Analytics Club, Lviv .Net, GDG Lviv, WTM Lviv, IT Arena)
• Received a scholarship as one of the top-5 performers from my faculty every year since enrollment (2017 - 2021).
• I am a founder and organizer of tech summer camps for teenagers. Organized four camps in 3 cities since 2018.
• Awarded membership of Junior Academy of Sciences of Ukraine for my research in economics in 2017
• Received a scholarship for international studies and participated in SOL program in Bideford, GB in 2015.
• Currently, I'm working as a product analyst in an SF-based international product company. I work with customer analytics: funnel analytics; retention analysis; LTV analysis; A/B testing design, implementation, and analysis; user experience analysis to suggest and help implement data-driven improvements for the product and drive business metrics.

• My previous experience was mostly working with consulting projects, which included working with marketplace data, production data analysis, building predictive models for business purposes, developing demos and iterative reporting. I used Python (pandas, numpy, scikit learn, plotly, etc.), R, Dash, Jupyter Notebooks, worked with SQL and Google BigQuery.

• I have a background in academic research in economics and finance. My last paper was about probabilistic methods for predicting the expected maximum stock price for a defined period. The work is focused on optimal stopping theory and usage of dynamic binomial random walks. The source code for the project was developed in R programming language.

• I have a Bachelor's degree in Information Technology and Business Analytics from UCU. My academic background includes but is not limited to calculus, statistics, programming, algorithms, linear algebra, econometrics, and finance.

• I have also worked on some personal projects on the following topics: analytics on Ukrainian governmental open data (ЄДРСР, ЄДРД НАЗК), comparison of different classification methods for startup success prediction, automatic text summarization for Ukrainian language, automated risk assessment system for ProZorro.

• Generally, I worked with the following methods and techniques:
- Regression Analysis (OLS and logistic regressions, multiple regression analysis for cross-sectional data as well as for time series, following OLS assumptions, dealing with dummy variables)
- KNN, PCA, SVM, LDA
- Cohort Analysis
- Sentiment Analysis
- TF-IDF
- Network Analysis
- Statistical Hypothesis Testing
I prefer remote-first working environments.