Лариса

Larysa Koriahina
Data Analyst
[відкрити контакти](див. вище в блоці «контактна інформація») [відкрити контакти](див. вище в блоці «контактна інформація») [відкрити контакти](див. вище в блоці «контактна інформація») Kyiv, Ukraine

SUMMARY SKILLS
Data analyst with a strong engineering background and over 20 years of HARD SKILLS
business experience (sales, finance, e-commerce). I specialize in SQL, Python, Advertising Companies Analysis,
transforming complex data sets into strategic business solutions. I am
Gathering of the Requirements, Theory of
proficient in SQL, Python, and BI tools for product and marketing
optimization. Probability and Mathematical Statistics, A/B
Tests, Product Analysis, Business Metrics(LTV,
Retention Rate, Churn Rate, CAC, Conversion
PROJECT EXPERIENCE Rate, ARPU), Data Visualization, Data
User retention assessment based on cohort analysis Storytelling, Data Cleaning & Validation
01/2026
https://bit.ly/project-user-retention-assessment TOOLS
Amplitude, Google Analytics, Tableau,
Tools: SQL,Google Sheets
Description: Creating a user lifecycle analysis tool to compare the Looker Studio, Power BI, Pandas, NumPy,
behavior of users who were recruited organically and those who Matplotlib, Seaborn, Jupyter Notebook,
came through advertising campaigns, using the cohort analysis BigQuery, Google Sheets, Excel
method.
My tasks: Data processing and visualization SOFT SKILLS
User behavior analysis
Accurate, Committed, Determined,
Providing retention improvement recommendations
Meticulous
Result: An automated dashboard has been created that allows you
to assess audience loyalty in one click
LANGUAGES
Facebook Ads Performance & Marketing ROI Analysis
02/2026
English - Intermediate, Ukrainian - Native
https://bit.ly/project-facebook-ads-performance
Tools: Python (Pandas, NumPy, Matplotlib, Seaborn)
Description: Comprehensive analysis of the effectiveness of
advertising risks on Facebook based on historical data for 2021. EDUCATION
My tasks:
Calculate and visualize the dynamics of ROMI and costs over time.
Perform statistical analysis of the distribution of profitability indicators Data Analyst
(histograms and Box plots).
Build a linear regression model to visualize the dependence of income IT School GoIT
on costs.
12/2025- 06/2026
Result: An analytical report has been generated that helps redistribute
the budget in favor of the most effective channels.
Specialist, mechanical engineer
WORK EXPERIENCE Igor Sikorsky Kyiv Polytechnic Institute
Business Owner (E-commerce) 1955 - 2001
Unihouse
01/2013 - now Kyiv, Ukraine
Analysis of the sales funnel and key performance metrics: Creating a
system for monitoring indicators (conversion rate, ARPU, Retention)
using Google Analytics 4 and Google Sheets, which allowed us to
identify problems at the order processing stage.
Research and regular analysis of the market of competitors: Monitoring
prices and assortment of competitors, adapting the pricing strategy in
real time.
Demand forecasting and stock management: Using sales data to build
predictive demand models.
Supply chain optimization based on transportation cost analysis.

Achievements:
Combining data from advertising cabinets (Google Ads, Facebook) and CRM
systems. This allowed to accurately calculate CAC and ROAS for each traffic
source.
Optimization of marketing costs. Due to the redistribution of the budget to
advertising channels with higher LTV, the overall CAC decreased by 18%.
Growth of the average order value. Analysis of related products was
implemented, which allowed us to improve the effectiveness of
recommendations and increase AOV by 12%.