Veselin Lilov
Data Analyst and Python builder creating analytics platforms, machine learning systems, and web products with clear business purpose.
I turn data, APIs, dashboards, process automation, and product logic into reliable systems built for real users and operations.
About Me
I design systems with structure, maintainability, and business value in mind, from data models and reporting layers to APIs, process automation, and usable product workflows.
My strength is combining analytical thinking with technical execution across analytics, machine learning, and full web application delivery for real business use.
Analytics & ML Projects
Debt & Risk Intelligence Hub
Debt analytics, acquisition review, and collections strategy platform with import validation, risk scoring, valuation workflows, dashboards, reporting exports, and next-best-action planning.
Dashboard, valuation, and collections strategy preview
Portfolio import, debtor scoring, valuation logic, collector queue review, strategy simulation, dashboards, exports, and API-driven reporting built as one decision-support product.
Live demo: first load may take 20-30 seconds.
Churn Revenue Risk Production Platform
Customer churn and revenue-risk intelligence platform for customer scoring, revenue exposure analysis, monitoring, and protected browser-based review workflows.
Executive dashboard preview for churn scoring and revenue-at-risk monitoring
Built to turn churn prediction into operational decision support through customer risk scoring, revenue-at-risk outputs, monitoring workflows, and internal control surfaces.
Fraud Monitoring Production System
Machine learning system for fraud prediction, expected loss estimation, monitoring, API scoring, business-facing reporting, and production-style risk review workflows.
Concept preview for fraud scoring, monitoring, and reporting
Real-time fraud scoring, expected loss estimation, monitoring workflows, and reporting designed for a production-style ML risk environment.
Process Automation Projects
Data Quality Monitoring Pipeline
Automated data quality monitoring pipeline with PostgreSQL checks, Excel reporting, email alerts, scheduler support, and Power BI-ready outputs.
Power BI quality monitoring dashboard preview
Built to automate data quality checks, execution logging, Excel reporting, alerting, and business-facing monitoring from one production-style pipeline.
KPI Automation Pipeline
Automated KPI reporting pipeline that extracts PostgreSQL data, validates and transforms it in Python, emails Excel reports, and feeds Power BI dashboards.
KPI reporting and executive dashboard preview
Designed to replace manual KPI reporting through scheduled extraction, data validation, formatted Excel delivery, and direct Power BI visibility.
RPA Process Automation Pipeline
Python and Selenium automation pipeline for secure browser login, data extraction, pandas processing, Excel reporting, and batch execution workflows.
Browser automation and reporting workflow preview
Simulates a real operational automation flow with secure login, raw data capture, transformation, report generation, and execution logging.
Web Applications
BookZone
Online bookstore with catalog, search, cart, orders, discount logic, and customer-facing e-commerce workflows and storefront interactions.
Homepage preview of BookZone
Catalog browsing, search, cart behavior, checkout flow, and store administration combined into a complete e-commerce experience.
EventHub
Event platform with ticket sales, online payments, seat selection, map logic, QR validation, and structured event booking workflows.
Homepage preview of EventHub
Ticket sales, seat selection, payment flow, and QR-based event entry brought together in one structured event platform.
Paradise Food Order App
Internal food ordering system built for the Bulgarian company Matraci Paradise, with quantities, limits, permissions, and admin summaries.
Menu and ordering preview
Internal ordering workflow built for Matraci Paradise, combining daily menu operations, quantity limits, permission rules, and admin reporting for practical day-to-day use.
Applied Skills
Data Analytics
Python, SQL, KPI logic, reporting, dashboard analysis, process automation, and decision-support workflows
Machine Learning
Scoring models, fraud analytics, model monitoring, drift checks, and business-facing ML workflows
Process Automation
Scheduled jobs, reporting automation, monitoring flows, internal process logic, and browser-based operational workflows
Data Layer
PostgreSQL, SQL, structured data models, analytics marts, and reporting-ready data layers
Front end
JavaScript, HTML, CSS, responsive UI, product-facing flows, and clean application interfaces
Back end
Django, FastAPI, REST APIs, business logic, admin flows, process automation, and production-style backend delivery