Tevin Shaduka

Available to hire

I’m a results-driven QA and data-minded professional who specializes in breaking down live digital ad experiences and proving issues with rigorous, evidence-graded testing.

About

I’m a results-driven QA and data-minded professional who specializes in breaking down live digital ad experiences and proving issues with rigorous, evidence-graded testing. From Meta Ad Library and landing-page validation to detailed click-path reproduction, I focus on what actually happens after an ad is clicked—then I document the root cause clearly with screenshots, timestamps, and plain-language fixes.

In my recent work, I’ve run repeatable QA sweeps for live Meta campaigns, targeting failure patterns like broken pages, sold-out/expired offers, redirects, and pricing mismatches. I also support marketing and decision-making work by turning real campaign performance data into clear research findings, audit-ready reporting, and stakeholder-friendly deliverables—while maintaining strong sourcing practices and stress-testing claims before sharing them.

  • Joined October 2026

Industry experience

  • Software & Internet
  • Professional Services
  • Retail
  • Media & Entertainment
  • Financial Services
  • Education
  • Consumer Goods

Projects · 2

The Brief (self-initiated): Find out what customers actually reach when they click live Meta ads for DTC brands, and prove every failure well enough that a brand could verify it without taking my word for it. What I Did Pulled active ads from Meta's public Ad Library. No account access, only what any customer can see. Followed every ad link the way a customer would: US connection, 390 px phone. Compared what each ad promised with what the page delivered: missing pages, redirects to the homepage, retired or sold-out products, re-listed items. Reproduced every finding twice, at least an hour apart. Anything I couldn't reproduce was cut. Graded each finding by severity and recorded the ad, landing URL, time checked, evidence and a plain-language fix. What Came Out An 8-page field-notes report covering six real failure patterns, checked 29 Sep to 1 Oct 2026. The lead case is nine active ads for one brand, all pointing at a product page that returns 404. Brands are anonymised; findings are dated and have not been re-dated. Read It Here: https://www.twine.net/signin The service: https://www.twine.net/signin Method in one line: Sources and check times on every finding, confidence stated, unknowns left as unknowns.

  • Data Analyst
  • Marketing Analyst
  • QA Engineer

The Brief (self-initiated): Build a data-led digital PR story from free public data, then try to break it before an editor can. The Question: Which UK cities spend the most of this winter commuting in the dark? What I Did Calculated sunrise and sunset for 34 UK cities on every one of the 154 days of winter time (25 Oct 2026 to 27 Mar 2027). Defined a "double-dark day" as sunrise after 08:00 and sunset before 17:00, then counted them per city. Checked the results against an independent source. Tested the obvious headline, "the further north, the darker the evening". The data contradicted it on 83 of 154 days, so I cut it. What Survived Scotland takes the top five. Inverness has 86 double-dark days; Brighton has 22. The east loses its evenings last. Norwich is the last of the 34 cities to see a 5:30pm sunset again (28 Feb), six days after Inverness. Norwich's sun sets earlier than Inverness's on 83 of the 154 days. Delivered Ready to Pitch: Headline findings, an interactive chart set, a full 34-city ranking, a downloadable dataset, and an 8-page method note covering sources, limits and pitch angles for national and regional desks. See the Study: https://www.twine.net/signin · Data (CSV): https://www.twine.net/signin Method in one line: Every number traces to a source and a calculation an editor can follow, and what the data can't show is stated, not filled in.

  • Data Analyst
  • Data Visualizer
  • Marketing Analyst

Work experience· 4 roles

Founder, Paid-Ad Leak Sweeps · Tevin Research / toog.proSep 2026 – Present · 3 mos

Run remote, evidence-graded QA sweeps for live Meta campaigns. Pull active ads from Meta’s public Ad Library, follow links from a US connection on a 390px phone, and compare the ad’s promise with the landing page. Check for broken pages and redirects to the homepage, sold-out or retired products, expired offers and codes, and ad-versus-page price mismatches. Publish field notes and reproduce failure patterns to confirm issues, including severity ranking and plain-language fixes.

Research Analyst · US marketing agency (via contractor, white-label)Jan 2026 – Present · 11 mos

Delivered audience and campaign intelligence reporting for clients across automated, retail, consumer goods, and housing sectors. Produced agency-ready wrap reports using real campaign performance data, replacing placeholder insights with evidence-backed findings, and tailored reporting to each client’s format and deadlines.

Founder and Principal Analyst · toog Decision SystemsJan 2026 – Present · 11 mos

Run evidence-graded research practices where each claim traces back to a primary source and is stress-tested before being shipped. Designed and shipped the firm’s service websites, including a web redesign and a data-research line, ensuring research delivery is reproducible and client-ready.

Technical Analyst · Private InvestorsJan 2019 – Jan 2021 · 2 yrs 1 mo

Education

Diploma in Audio Engineering · Boston College, Cape Town2014 – 2016

Certifications and awards

Technical and QA evidence grading approach (severity-ranked defect reporting, including ad/landing URL, timing, screenshots, and plain-language fixes)2024 – 2026

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