Валерія

VELYCHKO VALERIA
DATA ANALYST
I am a young and goal-oriented data analyst with strong analytical skills. I have expertise in SQL, Python, and data
visualization using Tableau. I have hands-on experience working with large datasets in BigQuery and creating
insightful dashboards. I am proficient in Google Sheets, effectively utilizing advanced functions like SUMIF,
VLOOKUP, and FORECAST to streamline analysis. I possess a solid understanding of A/B testing theory, which I
apply to analyze experiments and provide actionable insights. My expertise lies in solving analytical tasks and
optimizing data-driven processes.

CONTACTS PROJECT EXPERIENCE
[open contact info](look above in the "contact info" section) Google Sheets
Based on the activity sheet, a cohort was created with the Activity
[open contact info](look above in the "contact info" section)
month number (the number of months from First activity month to
Telegram Activity month) and unique users. Then the line chart was created,
LinkedIn which shows a decrease in the number of users. In addition, based on
the activity sheet, a pivot table was created on which First activity
Kozyatyn, Ukraine
month and Activity month number and unique users are displayed. A
table with percentages is created at the bottom. Both tables display
HARD SKILLS retention rate.
Mathematics SQL
Data Visualization Developed SQL queries to process transactional data and calculate key
A/B testing metrics such as MRR, ARPPU, Churn Rate, LTV, and
Expansion/Contraction MRR. The script aggregates data on a monthly
Data Manipulation and Analysis
basis, identifies new and churned paying users, and uncovers the
Statistical Analysis drivers behind revenue changes. The resulting dataset serves as the
Database Management foundation for dashboard visualization.

Understanding of Customer Journey
Tableau
Map and creating of tracking plan Built an interactive Tableau dashboard featuring at least 7 charts,
including visualizations that break down changes in revenue and paid
TOOLS users month over month. The dashboard includes filters by date, user
Tableau.Public language, and user age. It enables product managers to monitor
DBeaver(PostgreSQL) revenue dynamics and perform high-level analysis of key business
Anaconda.Jupyter Notebook drivers.
Google Clouds (Big query,
Google Colab)
Python
Google Sheets Advertising Campaign Performance Analysis: Examined ad spend and
ROMI trends in 2021-2022, using visualizations with rolling
SOFT SKILLS averages. Grouped data by campaign to assess total spend and ROMI.
Analyzed ROMI distribution through box plots and histograms.
Punctuality Conducted correlation analysis to identify key relationships between
Logical thinking numerical metrics. Applied linear regression to evaluate the
Analysis and decision making relationship between ad spend and revenue.

LANGUAGES A/B testing
Collecting and analyzing data on the number of users, conversions,
English - Intermediate and conversion rates in groups A and B in Python. Selecting an
Ukrainian - Native appropriate statistical test, calculating the test statistic and p-value,
and assessing the null hypothesis. Creating a visualization with 95%
EDUCATION confidence intervals to compare mean values between groups.
Drawing conclusions on the effectiveness of the tested changes.
IT School "GoIT" Additionally, generating a time-series chart to analyze conversion
Data Analysis 2024 rate trends over time.