A practical breakdown of the skills, tools, and working style behind my AI-enabled Technical Operations work.
Back to HomePractical "Can-Do" approach to messy operational problems, with a focus on finding the logic between the dots and turning it into usable workflows.
Fast learner who picks up new tools quickly and applies them to real business, data, and operations problems.
Comfortable connecting commercial, operations, product, data, and technical teams around shared workflows and clear execution.
Fluent bilingual professional (English and Hebrew).
Hands-on use of Claude, Claude Code, ChatGPT, Gemini, and Google Antigravity for analysis, prototyping, workflow design, content cleanup, and structured data work.
Using AI-assisted coding environments to build internal tools, dashboards, scrapers, data engines, and proof-of-work prototypes quickly.
Designing parallel AI-assisted workflows for review, enrichment, classification, export, and high-volume processing.
Building practical tools such as taxonomy agents, PIM export pipelines, product data engines, and lightweight tracking systems to reduce manual work.
Hands-on operational expertise across Shopify, WooCommerce, Mirakl, Rithum/DSCO, Radial, LogicBroker, and Cymbio-style product data workflows.
Mapping product data, variants, attributes, images, inventory, pricing, and taxonomy logic across marketplace and retailer requirements.
Navigating onboarding, compliance, template, taxonomy, and EDI/API requirements for Nordstrom, Macy's, Bloomingdale's, Farfetch, Shop Premium Outlets, and related channels.
Managing daily marketplace data flows, catalog maintenance, retailer requirements, and cross-functional workflows using tools like Airtable, Asana, and Monday.com.
Experience managing a $2M+ annual operational budget, procurement, vendor negotiation, contracts, and operational cost reduction.
Authoring SOPs, templates, intake forms, QA checks, and repeatable workflows that make execution easier for teams.
Building visibility around inventory buffers, revenue, sell-through, margin protection, and operational KPIs.
Using AI tools for marketplace SEO, keyword generation, product content improvement, and retailer-ready text cleanup.
Strong Excel and Google Sheets capability for product data cleanup, lookup logic, QA, mapping, reporting, and operational analysis.
Using SQL, Python automation, and Google Apps Script for data transformation, validation, scraping, export, and workflow automation.
Designing schemas, identifying search keys, normalizing attributes, finding anomalies, and translating messy product data into clean operational structures.
Building KPI dashboards in Power BI and lightweight internal tools with HTML/CSS, Apps Script, Python, and AI-assisted coding.
Practical experience validating API, EDI, CSV, XML, and JSON flows, including troubleshooting mismatched attributes and mapping logic.
Building workflow automations with Make.com, Zapier,, Apps Script, Python, spreadsheets, and APIs.
Reading JSON/XML/API responses and operational error patterns to isolate root causes and coordinate fixes with technical teams.
Basic MCP familiarity and hands-on use of AI coding, local scripts, APIs, and deployment tools for practical automation work.