Sam Okafor
Freelance Data Annotator · QA Lead
Solid annotation foundation with documented QA workflow ownership. Misses the top tier on technical depth and a published methodology, but a credible candidate for most vendors today.
Clear written updates to clients and pod leads.
Uses structured QA frameworks; some metrics quoted.
Comfortable with Sheets + light Python, no notebooks.
Independently researches edge cases before flagging.
Workmanlike writing — improves with structure prompts.
Two years of e-commerce taxonomy expertise.
Consistent contracts and renewals.
Long-term remote with EU+US overlap.
Reviews LLM outputs but not via formal rubrics.
Owns labeling QA loops across 6-person pod.
- · Owns the QA loop for a 6-person annotation pod (rare on most resumes at this level).
- · Quantifies impact: 'cut rework by 22%', 'lifted inter-annotator agreement 0.69 → 0.78'.
- · Strong remote work record with overlapping US + EU coverage.
- · No formal rubric design experience beyond inheriting client templates.
- · Light on Python — limits eligibility for evaluator + light engineering roles.
- · No public artifact (blog, write-up, talk) to validate methodology.
- 1Publish a short 'How I QA my pod' write-up — drop a link into the header.
- 2Take one Python-for-evaluators course; add a quantified project bullet.
- 3Re-target Scale AI and Surge AI with a referral within 30 days.
- 4Shift headline to 'QA Lead — LLM Evaluation' and lead with rubric work.
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