Sec. 04 — First 30 / 60 / 90 · what I'd close, ship, and give back

Prescription · forward-looking plan; resume evidence at the bottom

The capacity line at the bottom of the JD.

The success criteria in the posting end with this: "Channel owners regain measurable capacity for strategy because technical coordination, detailed execution, and analysis are handled." That's the single sentence I optimize for. Here's how I'd spend the first 90 days making that line real — grounded in what I already saw on petsafe.com, sized to a specialist role, and honest about what I would not touch.

Window	What I ship	How it maps to the JD	Status
Days 1–14 Listen	Shadow one launch end to end (whichever brand is next). Read every existing Tableau workbook and note what's trusted, what's stale, what nobody looks at. Meet the CRM, SEO, brand, and dev leads. Read the roadmap. Ask questions, don't propose.	PM & ops; measurement plans; the boundary rules from the JD (channel owners keep strategy).	Now
Days 15–30 Close the front-door tickets	Homepage JSON-LD (Organization + WebSite + BreadcrumbList). Fix /sitemap.xml so it serves XML. Publish a /llms.txt. Ship a UTM taxonomy sheet and get sign-off. Baseline the "elbow grease" backlog into a single tracker.	"Elbow grease" cleanup; UTM discipline; documentation; SOPs; the "trusted definitions" prerequisite.	Now
Days 31–60 One trusted dashboard	Stand up (or refactor) one Tableau workbook that reconciles Shopify ↔ GA4 ↔ Triple Whale daily, with a red flag when they disagree >3%. Publish the metric dictionary next to it. Ship the campaign brief template + pre-launch QA gate as a working artifact. Run one AI-assisted anomaly scan per week and validate the outputs.	Tableau; GA4; Triple Whale; approved AI usage (Claude/ChatGPT with validation); campaign QA.	Next
Days 61–90 Give capacity back	Absorb the recurring "coordinate this promo" work from the CRM and SEO leads so they get their afternoons back. Own end-to-end delivery of 2 campaigns from intake to close, with post-launch readouts in prose. Start a prioritized experimentation backlog with hypothesis + measurement plan for each item.	The capacity line. Recurring readouts. Experimentation. All measurable.	Later

What I would not do

Why I already fit

A short pattern-match from my resume to the four JD buckets — no fluff.

JD bucket	Evidence from my work
Technical PM & ops	Led Universal Wholesale's migration from a legacy HTML catalog to a B2B ordering platform: 14,000+ product records prepared, validated, and imported with repeatable cleanup / exception-tracking / QA processes. Owned intake through launch.
Data analysis & Tableau-adjacent	GA4 + Search Console are my daily view for reporting today. I run weekly rollups with Claude and ChatGPT to spot anomalies (with validation) and build my own catalog QA tools — one is CSV Mapper, live at mousabatarseh.com/csv-mapper.
DTC & Shopify ops	Three years on Shopify — currently the United Textile Wholesale storefront (Ferndale, MI), previously as part of Universal Wholesale's platform work. Collections, coupons, seasonal promo calendars, pre-/post-launch QA, and the catalog data behind all of it.
Measurement, testing, continuous improvement	Five years of on-page SEO and content ops, structured data, canonical / sitemap hygiene across my own domains (mousabatarseh.com and work.mousabatarseh.com — public PageSpeed & Search Console evidence available on request). Documented and versioned, not one-off.