Viktoriia Levytska

Data Analyst · Data Scientist · AI-assisted Automation

I build data projects that connect business questions, analytical thinking, machine learning and practical automation.

Featured projects

Project	What it demonstrates	Status
Olist — E-commerce Analytics	Business & product analytics, e-commerce KPIs, customer/seller analysis	✅ Live demo
ReverPro — International Comparative Analysis	International benchmarking, public-sector analysis, decision support	🚧 Portfolio publication in progress
Graal — Predictive Modeling	Machine learning, predictive modeling, model evaluation	🚧 Portfolio publication in progress
Trading Automation	Telegram signal processing, exchange API automation, risk controls, AI-assisted development	🔒 Case study available; code under security review
TaxiFare — Big Data & ML Pipeline	Big Data workflow, cloud-oriented ML pipeline, model serving	🚧 Portfolio publication in progress

Olist — E-commerce Analytics

A business-oriented analytics project built around the Brazilian Olist e-commerce dataset. The portfolio version focuses on translating data into actionable business insights.

Live: https://ladyinet.fr/olist/

ReverPro — International Comparative Analysis

A real-world analytical case focused on an international comparative study within the ReverPro context. The portfolio version will present the methodology, comparative framework, findings and visual evidence without exposing confidential material.

Graal — Predictive Modeling

A machine-learning project focused on the predictive modeling workflow: problem framing, preparation, experimentation, evaluation and interpretation.

Trading Automation

An automation project connecting Telegram trading signals with structured validation, risk controls and Bybit order execution.

My role focused on requirements, workflow design, testing, validation and iterative project management, with implementation supported by AI coding tools.

TaxiFare — Big Data & ML Pipeline

A Le Wagon educational project used to demonstrate working with larger-scale data and an end-to-end machine-learning workflow, including cloud-oriented data processing and model serving.

What this portfolio is designed to show

• Business analytics: turning datasets into decisions and recommendations
• Data science: predictive modeling, evaluation and interpretation
• Data engineering mindset: reproducible pipelines and larger-scale data workflows
• Automation: APIs, Telegram workflows and external-system integration
• AI-assisted delivery: defining requirements, supervising implementation, testing and validating results

Current portfolio status

This profile is being actively structured for professional use. Selected projects are being published progressively with concise documentation, reproducible code where appropriate, and visual results.