Sedin Sehic
Python Automation Specialist | ETL, AI Pipelines & Data Work
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Built NOCTA Audio, a production-ready e-commerce demo for a premium audio brand. All 109 products are fictional, created for portfolio presentation only. Custom React + TypeScript storefront with catalog, filters, cart, checkout, wishlist, reviews, blog, and admin dashboard (analytics, product CRUD, order management). Developed alongside a connected Shopify store setup for the same brand — showing skills in both custom headless commerce and Shopify merchant workflows. Live: nocta-audio.vercel.app (http://nocta-audio.vercel.app) | Admin: /admin (admin/admin123)
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CommerceFlow is a founder-led B2B analytics product I designed and built for ecommerce teams using fragmented Excel exports. Flow: import sales/products/inventory → Run Your Analysis → executive dashboard + formatted Excel export (profit leakage, inventory, alerts). Stack: Python, FastAPI, deterministic analytics, guest sample workspaces. Deployed live on Render. https://commerceflow-1.onrender.com (synthetic data for evaluation).
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Built NOCTA Audio on Shopify (Dawn): 30-product catalog via CSV, homepage in index.json (hero, categories, trust, story, newsletter), and custom CSS/JS for dark luxury branding (Syne/Inter, gold accents). Created custom Liquid section nocta-featured-eight to show 8 products in fixed order without collection CSV import. Fixed Dawn schema errors (inline_richtext vs richtext). Delivered header-group, theme integration, and setup docs. Result: production-ready store with consistent branding and editable homepage sections.
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Built a Python automation that transforms Excel inventory into eBay-ready bulk listings. Automatically generates titles, descriptions, pricing, and categories from raw data. Removes manual listing work and enables scaling to 50+ products/day with consistent, structured output.
Skills and deliverables
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Built a custom eCommerce intelligence platform for analyzing large-scale sales, inventory, and product datasets.
The system detects profit leakage, dead inventory, low-margin products, stock risks, and operational anomalies through automated analytics workflows.
Features include:
• Executive KPI dashboards
• Product intelligence scoring
• Inventory risk analysis
• Alerts & recommendations engine
• Enterprise Excel report exports with charts
• Automated dataset processing pipeline
Designed for high-volume retail analytics and operational decision support.
Skills and deliverables
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Built a Python system that extracts structured data from PDF reports and generates clean, automated outputs (Excel + PDF).
Demonstrates a full pipeline:
PDF → extraction → structured data → interpretation → final report.
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Built a production-style E-commerce Data Pipeline & Analytics System.
The system processes multi-channel sales data (Amazon, Shopify), cleans and structures it, and generates business insights via API, dashboard, and Excel reports.
Includes real-time analytics (revenue, profit, margins), automated reporting, and inventory monitoring.
Designed to simulate real-world business workflows and replace manual data analysis.
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