Anastasiia

Anastasiia Nahoha
Data Analyst
Kyiv, Ukraine • [відкрити контакти](див. вище в блоці «контактна інформація») • [відкрити контакти](див. вище в блоці «контактна інформація») • [відкрити контакти](див. вище в блоці «контактна інформація»)
Data Analyst with 5+ years of experience across media measurement and retail category analytics. Specialises in turning complex
commercial and classification data into clear, actionable recommendations, from SKU and assortment performance evaluation
to root cause analysis and process automation. Works closely with category teams, stakeholders and management; strong in
Python, Excel and NielsenIQ.

Areas of Expertise
Retail: Category & Assortment Analytics • SKU Performance Evaluation • Private Label Analysis • Forecasting & Trend Analysis
Data & Reporting: Data Visualisation & Statistical Analysis • Dashboard Development • Report Automation • Data Cleaning
Business: Root Cause Analysis • Financial & Operational Analysis • Requirements Gathering • Cross-Functional Collaboration

Professional Experience
Fozzy Group (Silpo), Kyiv, Ukraine 08/2025 – 10/2026
Specialist, Commercial Office (Palette Project)
Enhanced assortment and category performance across Food, Non-Food and Private Label by building analytical models for SKU
efficiency and assortment gap analysis, translating commercial data into actionable recommendations for category teams.
Key Accomplishments:
• Developed Private Label SKU efficiency evaluation, evolving a manual Excel algorithm into an automated Python model run
quarterly across all departments; cut analysis time from 3 days to 4 hours and informed SKU-level decisions.
• Piloted and implemented a stock clearance project at a single branch for Home Goods, the chain’s category with the largest
share of remnants and discontinued assortment: cut inventory by 30% within a quarter while holding a 10–15% margin.
• Evaluated Food and Non-Food categories by analysing commercial KPIs, dynamics, and SKU and market performance,
identifying assortment gaps and proposing growth initiatives that increased revenue, volume and margin.
• Delivered ad-hoc analytical projects, from assortment restoration templates to assortment reduction and prioritisation
analysis across Silpo clusters; automated recurring tasks in Python (Jupyter) and built custom NielsenIQ views.
Nielsen, Kyiv, Ukraine 05/2021 – 05/2025
Classification Analyst
Streamlined daily media streaming data analysis on internal platforms, rectified inaccurate classifications across streaming
brand datasets and delivered insights to resolve client-specific issues.
Key Accomplishments:
• Enhanced data pipeline performance by automating and refining existing scripts, reducing manual intervention.
• Executed Saudi Arabia streaming classification initiative by engineering culturally relevant content rules and verifying
accuracy via targeted household testing, delivering over 95% accuracy from initial deployment.
• Uncovered root causes of a 40% spike in YouTube streaming metrics via household-level anomaly tracking and classification
reviews, enabling precise data correction and elevated client reporting standards.
• Led onboarding of a 15-member team by authoring SOPs and running interactive training, enabling independent handling of
70% of tasks within one month; framework later institutionalised for team scalability.

Education & Certifications
Masters of Science in Computer Science 2020 – 2022
Igor Sikorsky Kyiv Polytechnic Institute (KPI), Institute of Applied System Analysis (IASA), CAD
Bachelor of Science in Computer Science 2016 – 2020
Igor Sikorsky Kyiv Polytechnic Institute (KPI), Institute of Applied System Analysis (IASA), CAD
Statistics For Data Analysis Using Excel (Accredited) | Udemy 2024
Business Analysis "A TO Z" Masterclass | Udemy 2024
Business Analysis Fundamentals - ECBA, CCBA, CBAP Endorsed | Udemy 2023

Technical Proficiencies & Languages
Data Analysis: Python (Pandas, NumPy, Jupyter), SQL (basic), R, Excel (Pivot Tables, formulas), Statistics, NielsenIQ, Spotfire
Dashboards, internal Nielsen data platforms
Visualisation: Plotly, matplotlib, Tableau
Languages: Ukrainian (Native) | English (B2, Upper-Intermediate)