Key Skills

Freelancer Overview

I bring a strong blend of quantitative research, automation engineering, and data quality rigor that maps directly to high‑precision AI training data and labeling workflows. At Avnet, I designed OCR and information‑extraction pipelines (pdfplumber, Tesseract, pandas) with 95%+ field‑level accuracy across heterogeneous PO/invoice templates, enforcing business‑rule validations, exception routing, and auditable logs at 5,000+ docs/month scale. I’ve built resilient RPA with UiPath/Python/SQL, robust session management, and CV‑based challenge classification—experience that translates to data governance, label schema enforcement, edge‑case handling, and production reliability for labeling platforms. Previously as a quantitative researcher/developer, I created multi‑market datasets (tick and minute), engineered features, and validated strategies across HK/US/JP/IN markets, which sharpened my skills in ground‑truth definition, annotation guidelines, and statistical QA. I routinely implemented anomaly detection, maintained short‑selling and tick‑level feeds, and authored reproducible data pipelines. Combined with strong scripting (Python, SQL, R, C++), ML exposure, and bilingual/cantonese communication, I’m adept at building high‑fidelity labeling instructions, programmatic pre‑labeling, quality audits, and scalable human‑in‑the‑loop workflows.

Labeling Experience

Education

Work History