Олена

Olena Filinova
Data Entry Specialist
Junior data professional skilled in data cleaning, verification,
and database management. Use MS Excel, Google Sheets,
SQL, and Python in my work. I enjoy finding patterns to
organize large amounts of data and automating routine
processes to maintain high data quality. Ready to apply my
technical skills and pedantry to ensure accurate and timely
data entry.
[відкрити контакти](див. вище в блоці «контактна інформація»)
[відкрити контакти](див. вище в блоці «контактна інформація») PROJECTS
Telegram: @El_Filinova Stack Overflow Developer Survey Analysis
LinkedIn: Link:
http://[відкрити контакти](див. вище в блоці «контактна інформація») https://colab.research.google.com/drive/14NqiQSMr0pPPO
Location: Nesebar, Bulgaria RwnDvvODB5Y8NM8CP?usp=sharing
Tools: Google Colab, Python (pandas).
HARD SKILLS Description: Analysis of central tendency measures, data
 Python analysis and grouping by criteria, visualization of analysis
 BI tools: Tableau, Power BI, Looker results in tabular form.
Studio Task: Filter data, group, sample by parameters, determine
 Excel/ Sheets: formulas, pivot tables, the total number of survey participants, calculate central
charts tendency measures of the parameter.
 A/B testing Result: Formed an analytical report in tabular form with key
 Data Storytelling: analytical insights and statistical metrics. Identified patterns between the skill level
visualizations and the tools used, which allows predicting trends in the
 Business metrics industry.

TOOLS User Retention Evaluation
 Google Analytics Link:
 Tableau, Power BI https://docs.google.com/spreadsheets/d/1sKtMEli4NUGaz1c
 Pandas, NumPy, Matplotlib, Seaborn, WqDkmnCWwcZ30TKR-8hz3KAFi2ik/edit?usp=drive_link
Jupyter Notebook Tools: Google Sheets, SQL
 BigQuery Description: Data cleaning and transformation, building and
 Google Sheets, Excel concluding on cohort tables.
Task: Clean data, adjust the date, create CTE tables, build
SOFT SKILLS an aggregated table.
 Responsible Result: Calculated Retention Rate metrics for various user
 Detail-oriented cohorts. Identified the most loyal customer segments.
 Meticulous Formed recommendations for improving the retention
strategy based on cohort behavior dynamics.
LANGUAGES
 English: Intermediate WORK EXPERIENCE
 Ukrainian: Native JSC "Ukrposhta" Labor Norming Engineer (2017-2019)
 Russian: Native  Sorted data for labor cost reports to evaluate department
performance.
EDUCATION  Controlled the collection of statistical data and its integration
 IT School "GOIT" — Data Analysis, into the company's analytical reports.
2026  Calculated salaries, bonuses, and allowances in specialized
 Odesa National Economic University software IS-Pro.
(2012 - 2016) — Master's Degree,  Prepared primary documentation for accounting.
Finance and Credit  Prepared data for forming and optimizing the staffing table.
 National University "Odesa Maritime  Processed and prepared data for analytical reports upon
Academy" (2006 - 2012) — Specialist's management request.
Degree, Radio-electronic systems and  Achievements: Optimized the data processing in Excel,
devices reducing the time to compile analytical reports by 20%.