Alina Matviichuk
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Kyiv,
Ukraine
available for hire
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I am a Data Analyst with hands-on experience working with data and a strong background in Excel, which I have gained in previous roles. I have 19 years of experience in finance and accounting, now pivoting into Data Analytics. I have experience managing complex financial operations, banking products, and credit portfolios for major corporations such as SOCAR. During my studies, I worked on data analysis, cleaning, and visualization, and I am continuously developing my skills in the tools required for a Data Analyst. Currently, my primary practical tool is Excel, but I am actively deepening my knowledge of analytics and am ready to apply it to real-world business challenges. Below is a description of the projects I have worked on.
Projects:
1. Cohort analysis and user retention to assess engagement.
Task: Assess user retention trends over 6 months in organic and paid traffic segments.
My role: Cleaning and standardizing non-standard date formats; developing a cohort model in SQL with monthly offset calculations (month_offset); calculating retention KPIs and creating an interactive reporting dashboard.
Tools: SQL (PostgreSQL), DBeaver, Google Sheets (pivot tables, filters, conditional formatting), cohort analysis, product metrics (retention rate, user segmentation).
2. Analysis of a Global Developer Survey.
Task: Conduct a comparative analysis of global developer compensation, the popularity of programming languages, and the demand for remote work based on the 2025 Stack Overflow survey (over 49,000 responses).
My role: Processed and cleaned a large dataset with mixed data types; performed exploratory data analysis (EDA); calculated demographic metrics and segmented financial metrics by industry and employment type.
Tools: Python (Pandas, NumPy), Jupyter Notebook, EDA, and statistical analysis.
3. Comprehensive A/B testing analysis to shape product positioning.
Task: To assess the impact of changing the value proposition (adding the text “50% off” while keeping the price at $4.99) on premium subscription conversions in the mobile app.
My role: Managed the full A/B testing cycle: calculated the experimental design (MDE = 15%, sample size = 18,336 users), filtered the target audience, ensured even traffic distribution, and statistically validated the results.
Tools: A/B testing, experimental design, Chi-square test, Python (SciPy, Statsmodels, Pandas), PowerPoint, product metrics (CR, ARPU, retention, refund rate).
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Portfolio
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45 USD Comprehensive design and analysis of A/B testing results
Python
Description: Evaluation of the impact of changing the price framing (adding a "50% discount" label while keeping the price at $4.99) on conversion to premium subscription in the mobile app.
My tasks:
Full cycle of development and analysis of A/B test: calculation of experimental design (MDE = 15%, sample size = 18,336 users), filtering of target audience, monitoring of traffic distribution uniformity, and statistical validation of results.
Result: A statistically significant increase in conversion was recorded from 6.10% to 8.90% (relative increase +45.9%), resulting in +278 additional customers. The reliability of the result was confirmed using the chi-square test ("χ" 2), ρ-value = 6.74*10^(-14) and no overlap in 95% confidence intervals. Retention metrics were analyzed (retention at 1/7 days, return rate), and a decision was made for full implementation, leading to an immediate increase in revenue and ARPU.
… Tools: Python (Pandas, SciPy, Statsmodels), chi-square test (χ 2), MDE calculation, analysis of cumulative metrics, product metrics (CR, ARPU, Retention, Refund Rate), PowerPoint.
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45 USD Analysis of the Stack Overflow Developer Survey 2025
PythonDescription: Conducted a statistical analysis of the Stack Overflow survey for 2025 (over 49,000 entries) to identify global trends in compensation, the popularity of Python, and the remote work market situation.
My tasks:
Data cleaning and EDA: Processed a large dataset (172 columns), working with mixed data types and missing values. Statistical analysis: Estimated metrics based on work experience and analyzed the popularity of Python among different age groups. Segmented benchmarking: Analyzed global salary levels and identified the highest-paying industries (Fintech, Software Dev) for remote positions.
Result: Developed a detailed profile of the current development market and identified the highest-paying industries (Fintech, Software Dev) for remote roles.
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45 USD Cohort analysis and user retention analysis
Description: A cohort analysis was conducted to evaluate user retention models and their activity based on a product dataset. Differences in behavior between organic and paid traffic segments were analyzed to identify factors influencing long-term user loyalty and to aid in business optimization.
My tasks: Data cleaning and extraction: Developed complex SQL queries using CTEs, CASE statements, and to_date functions to standardize non-standard date formats to a unified timeline for analysis. Cohort analysis: Built a cohort model by merging user registration data and events, calculated month offsets to track user activity over a 6-month period. KPI calculation: Calculated the retention rate for each cohort relative to the registration month, ensuring 100% accuracy of the baseline (Month 0). Dashboard development: Created an interactive reporting tool in Google Sheets using pivot tables, conditional formatting (heat maps), and slicers for dynamic filtering by user source.