Особисті дані приховані

Vadym Mosiichuk
Data Analyst

Kharkiv, Ukraine
Email: [відкрити контакти](див. вище в блоці «контактна інформація»)
LinkedIn: [відкрити контакти](див. вище в блоці «контактна інформація»)
Telegram: https://t.me/mine_telegram

SUMMARY:
Driven Junior Data Analyst with a solid foundation in product analytics, statistical research, and data
visualization. Combining hands-on experience in evaluating ad campaigns with a strong technical
mindset, I specialize in transforming raw data into actionable business insights. I leverage SQL, Python,
and modern visualization tools to identify user engagement drivers and discover product optimization
opportunities. My goal is to join a dynamic team where my analytical skills, commitment to data-driven
efficiency, and ability to handle complex data structures can directly support strategic business decisions.

HARD SKILLS:
Data Analysis & Statistics: SQL, Python, Theory of Probability & Mathematical Statistics, Data Cleaning
& Validation, A/B Testing.
Product Analytics & Metrics: Product Analysis, Gathering of Requirements, Business & Product Metrics
(Conversion, ARPU/ARPPU, LTV, Retention, Churn rate).
Data Presentation: Data Visualization, Data Storytelling, Tableau, Matplotlib, Seaborn.
TOOLS:
Tableau, Looker Studio, Power BI, Pandas, NumPy, Jupyter Notebook, BigQuery, Google Sheets, Excel.
SOFT SKILLS:
Accurate, Committed, Determined, Meticulous, Critical thinking.

PROJECT EXPERIENCE:
E-Commerce Sales Funnel & Conversion Analytics (GA4 & Tableau) (Link)
Tools: Google BigQuery (SQL), GA4 Event Schema, Tableau Public, Regex, Data Modeling,
Data Visualization.
Description: Developed an end-to-end GA4 e-commerce analytics dashboard (~867K rows)
analyzing a 7-step conversion funnel and marketing channels to optimize CR and ad spend.
My tasks:
● Data Pipelines (SQL/BigQuery): Unnested and transformed raw GA4 event logs using
CTEs and REGEXP_EXTRACT for URL parsing; built composite keys (user_pseudo_id +
ga_session_id) for accurate session tracking.
● Dashboard & Metrics (Tableau): Designed an interactive E-commerce Funnel dashboard
with custom KPI cards (Sessions, Purchases, CR) and high-performance global filtering.
Result:
● Key Insights: Uncovered a ~78.8% drop-off at the top of the funnel (session to product view)
and established baseline performance metrics: 1.34% CR across 354.8K sessions and 4.7K
purchases.
● Business Impact: Delivered an interactive dashboard empowering marketing team to
optimize ad spend toward high-converting channels and user segments.

SaaS Revenue & User Growth Analytics Dashboard (Link)
Tools: PostgreSQL (DBeaver), Advanced SQL (CTEs, LAG/LEAD), Tableau Public, SaaS
Metrics & UI/UX Design.
Description: Designed an end-to-end SaaS financial analytics dashboard in Tableau Public to
monitor MRR dynamics, subscriber retention, and unit economics for product-driven decision-
making.

My tasks:
● Data Engineering (SQL): Extracted relational data using multi-level CTEs and window
functions (LAG, LEAD, DATE_TRUNC) to model monthly cohorts, payment shifts, and churn
events.
● Metric Modeling & QA: Calculated core SaaS metrics (MRR breakdown, ARPPU, LTV, Churn
Rates) and built a Tableau validation framework to guarantee 100% calculation accuracy.
● Advanced Visualizations & UX: Applied card-based UI/UX principles (Z-pattern hierarchy,
dual-axis charts, custom palettes) and global filters (Date Range, Age, Language) for seamless
interactive analysis.
Results & Business Impact:
● Identified Core Retention: Discovered Revenue Churn (17–22%) was lower than User Churn
(25–28%), proving high-value subscribers maintain high loyalty.
● Targeted Onboarding Bottlenecks: Pinpointed a retention drop in November (User Churn
spiked to 35.7%), shifting product focus from acquisition to month 3–4 churn prevention.

WORK EXPERIENCE:
VITORIA company: B2B/B2C Sales Manager: Pool & Water Treatment Equipment,
03.2018 - 06.2022
Revenue & Growth: Streamlined sales workflows for swimming pool and water treatment systems,
contributing to a 10% increase in monthly regional segment revenue.
Technical Analytics & Consultation: Analyzed clients' engineering requests to deliver data-backed
technical consultations on water purification, improving the lead-to-deal conversion rate by 12%.
Client Retention: Monitored B2B client feedback trends and cross-selling data, helping optimize the
maintenance solutions funnel and keeping the client retention rate high.

LANGUAGES:
● English: intermediate
● Ukrainian: native.
EDUCATION:
IT School GoIT — Data Analysis, 03.2026 - 09.2026
Master’s Degree in Transport Technologies (Specialization: Traffic Engineering and
Management) in Kharkiv National Automobile and Highway University, 2012